Subspecies of the protozoan parasite Trypanosoma brucei are the causative agents of Human African Trypanosomiasis (HAT), a debilitating neglected tropical disease prevalent across sub-Saharan Africa. HAT case numbers have steadily decreased since the start of the century, and sustainable elimination of one form of the disease is in sight. However, key to this is the development of novel drugs to combat the disease. Acoziborole is a recently developed benzoxaborole, currently in advanced clinical trials, for treatment of stage 1 and stage 2 HAT. Importantly, acoziborole is orally bioavailable, and curative with one dose. Recent studies have made significant progress in determining the molecular mode of action of acoziborole. However, less is known about the potential mechanisms leading to acoziborole resistance in trypanosomes. In this study, an in vitro-derived acoziborole-resistant cell line was generated and characterised. The AcoR line exhibited significant cross-resistance with the methyltransferase inhibitor sinefungin as well as hypersensitisation to known trypanocides. Interestingly, transcriptomics analysis of AcoR cells indicated the parasites had obtained a procyclic- or stumpy-like transcriptome profile, with upregulation of procyclin surface proteins as well as differential regulation of key metabolic genes known to be expressed in a life cycle-specific manner, even in the absence of major morphological changes. However, no changes were observed in transcripts encoding CPSF3, the recently identified protein target of acoziborole. The results suggest that generation of resistance to this novel compound in vitro can be accompanied by transcriptomic switches resembling a procyclic- or stumpy-type phenotype.
Subspecies of the protozoan parasite Trypanosoma brucei are the causative agents of Human African Trypanosomiasis (HAT), a debilitating neglected tropical disease prevalent across sub-Saharan Africa. HAT case numbers have steadily decreased since the start of the century, and sustainable elimination of one form of the disease is in sight. However, key to this is the development of novel drugs to combat the disease. Acoziborole is a recently developed benzoxaborole, currently in advanced clinical trials, for treatment of stage 1 and stage 2 HAT. Importantly, acoziborole is orally bioavailable, and curative with one dose. Recent studies have made significant progress in determining the molecular mode of action of acoziborole. However, less is known about the potential mechanisms leading to acoziborole resistance in trypanosomes. In this study, an in vitro-derived acoziborole-resistant cell line was generated and characterised. The AcoR line exhibited significant cross-resistance with the methyltransferase inhibitor sinefungin as well as hypersensitisation to known trypanocides. Interestingly, transcriptomics analysis of AcoR cells indicated the parasites had obtained a procyclic- or stumpy-like transcriptome profile, with upregulation of procyclin surface proteins as well as differential regulation of key metabolic genes known to be expressed in a life cycle-specific manner, even in the absence of major morphological changes. However, no changes were observed in transcripts encoding CPSF3, the recently identified protein target of acoziborole. The results suggest that generation of resistance to this novel compound in vitro can be accompanied by transcriptomic switches resembling a procyclic- or stumpy-type phenotype.
Human African Trypanosomiasis (HAT; also known as Sleeping Sickness) is a disease endemic to sub-Saharan Africa, caused by subspecies of the parasitic protozoan Trypanosoma brucei. In addition, T. brucei brucei and T. brucei rhodesiense are infectious to livestock, causing Animal African Trypanosomiasis (AAT) [1]. Together, HAT and AAT account for a significant socio-economic burden across the sub-Saharan African continent. T. b. gambiense accounts for the majority (~98%) of HAT cases, and is endemic in 24 countries in west and central Africa [2], whilst T. b. rhodesiense causes the remaining infections and is restricted to east and southern Africa [3]. Whilst the rate of disease progression differs in duration between the two species, both begin with an early haemo-lymphatic stage of infection (stage 1), followed by a late-stage (neurological stage; stage 2), and without treatment, the disease is usually fatal [4].African trypanosomes display a complex life cycle that includes procyclic (PCF) stages in the tsetse fly as well as a mammalian-infective bloodstream (BSF) stage. Pleomorphic T. brucei strains are rapidly dividing in the BSF stage, with a long and slender morphology, but possess the ability to differentiate into non-dividing short stumpy forms, which are pre-adapted to survival in the insect vector [5]. This developmental transition is triggered by a quorum sensing mechanism involving a “stumpy induction factor”, recently identified as oligopeptide uptake mediated by the TbGPR89 transporter [6]. Differentiation between the various life cycle stages is accompanied by morphological changes, as well as global shifts in transcriptome and metabolome (including downregulation of BSF-specific variant surface glycoproteins - VSGs - and associated expression sites) [5,7-12]. Characterisation of the T. brucei life cycle stages has yielded the identification of several stage-specific markers. For example, stumpy-form T. brucei exhibits upregulation of transcripts encoding PAD (protein associated with differentiation) [9], as well as downregulation of histones, DNA replication/repair and cytoskeleton-related transcripts, indicative of their non-proliferative state [7,13]. In addition, both stumpy forms and PCFs express transcripts encoding EP and GPEET procyclins in place of VSGs [14]. Differentiation to stumpy form and PCF also involves downregulation of transcripts associated with glycolysis, as the parasite begins to shift to mitochondrial metabolism [8,12].Sustained efforts to control HAT have led to a significant reduction in T. b. gambiense case number. Whilst hundreds of thousands of cases were estimated at the millennium [15], only 992 were reported in 2019 [16]. Elimination by interruption of transmission of HAT is therefore a 2030 target in the WHO Neglected Tropical Disease initiative [17]. However, to realise this target for T. b. gambiense, and to be able to more efficiently treat cases of T. b. rhodesiense, safer drugs, preferably with oral bioavailability are needed to combat the disease. Historically, few chemotherapeutics have been available to treat HAT. Furthermore, some of those that are used currently are species (eflornithine) and disease stage-specific, with notable issues in administration routes, toxicity and emerging resistance [18-22]. The primary drugs used for stage 1 HAT are pentamidine and suramin, whilst melarsoprol, eflornithine and nifurtimox (the latter two now usually as a combination therapy against T. b. gambiense) are used to treat stage 2 infections [23]. None of these drugs are orally bioavailable and they involve long treatment regimens [24].Recent efforts have led to the development of two promising candidates, fexinidazole, which has now been licensed for use, but requires protracted 10 day administration [25], and acoziborole (AN5568 or SCYX-7158), a benzoxaborole currently in phase IIb/III clinical trials [18]. Benzoxaboroles are a relatively novel class of compounds, characterised by a boron-heterocyclic scaffold, which exhibits a broad spectrum of medicinal applications including anti-fungal [26], anti-parasitic [27-29], anti-viral [30] and anti-bacterial [31] activity.Several studies have shed light on the mode of action of acoziborole, as well as related benzoxaboroles. For example, the protein target of the anti-bacterial tavaborole (AN2690) was shown to be leucyl-tRNA synthetase [26]. Recently, a target of acoziborole and the livestock trypanocide AN11736, and also other benzoxaboroles [32], was identified as the trypanosome Cleavage and Polyadenylation Specificity Factor 3 (CPSF3), a nuclear mRNA processing endonuclease [33]. The same target was identified for the benzoxaborole AN3661, active against Plasmodium falciparum [34]. Our own studies showed that acoziborole treatment leads to significant perturbations in S-adenosyl-L-methionine metabolism in T. brucei, as well as further metabolic phenotypes similar to those elicited by the methyltransferase inhibitor sinefungin [35].In addition to mode of action, investigating potential mechanisms of drug resistance is crucial in optimising drug application in the field and prolonging the life time of chemotherapeutics [36,37]. Generation of resistance in an in vitro setting, when possible, has proven effective in predicting mechanisms of naturally acquired resistance in the field [38]. One previous study investigated mechanisms of trypanosome resistance against acoziborole, but the results were inconclusive, although amplification of the CPSF3 locus was observed in at least one acoziborole-resistant line [39]. In the case of the valyl-ester containing compound AN11736, which was in development for AAT [29], resistance has been shown to be due to loss of a protease that cleaves the parent prodrug to a carboxylate derivative that then accumulates to high levels leading to high levels of potency [40]. A similar prodrug cleavage mechanism was described for another trypanocidal benzoxaborole [41].In this study, the generation of an in vitro T. brucei cell line with high levels of resistance to acoziborole is presented. This cell line exhibited cross-resistance, as well as hypersensitivity, to several trypanocides, including increased resistance to sinefungin. Transcriptomics analysis of the resistant cell line revealed global upregulation of stumpy- or procyclic-specific genes and downregulation of BSF-specific genes, giving the appearance of a “stumpy” or “procyclic” transcriptome. No changes were observed in CPSF3 transcript abundance. However, the acoziborole-resistant cells retained BSF morphology. Analysis of the metabolome showed no changes in S-adenosyl-L-methionine levels in resistant cells treated with acoziborole, indicating that the metabolic phenotype of acoziborole treatment was abolished. In summary, acoziborole resistance, in vitro, appears to be characterised by global transcriptomic changes, leading to a partial switch towards procyclic mRNA abundances in resistant cells.
Results
In vitro selection of acoziborole-resistance
An acoziborole-resistant (AcoR) T. brucei cell line was generated by continuous in vitro culture of the Lister 427 strain. Notably, this strain is known to be monomorphic, and is incapable of differentiation through normal routes to procyclics via stumpy forms–including a failure to trigger mitochondrial oxidative phosphorylation [42,43]. Cells were cultured in the presence of incremental increasing doses of the benzoxaborole, starting at 170 nM (Fig 1). A wild-type cell line was also maintained in the absence of acoziborole to account for culture medium-derived artefacts or adaptation. After ~200 days, AcoR cells were viable in 4.96 μM of the compound (Fig 1A) and at this point, were deemed to be resistant compared to the parental control. At this point, the cell line was cloned by dilution for downstream experiments and four resistant clones were isolated. Cell doubling time was noticeably increased in all four clones, compared to a wild-type control (7.3 ± 0.43 h and 14.92 ± 3.19 h for wild-type and AcoR cells, respectively; Fig 1B).
Fig 1
Generation of an acoziborole-resistant cell line and analysis of cross-resistance.
A) Acoziborole resistance was generated in T. brucei Lister 427 cells through the addition of incremental concentrations of the benzoxaborole to cell cultures in vitro. Red line indicates mean wild-type EC50 for acoziborole. B) Cell density of the four AcoR clones, as well as a wild-type control, were monitored daily. AcoR cells were grown in the presence of 4.96 μM acoziborole and all cell cultures were passaged (seeding density of 2 × 104 cells/mL) when density reached 2 × 106 cells/mL. Cumulative cell density over a period of 5 days (120 hours) is shown (n = 3 per sample group). C) The AcoR line showed a significantly increased EC50 compared to wild-type cells. Mean EC50 was 4.88 ± 0.56 μM, approximately 25-fold higher than WT cells (EC50: 0.25 ± 0.01). Interestingly, AcoR cells also showed an increased resistance to the AdoMet-dependent MTase inhibitor sinefungin, which was shown to act in similar fashion to acoziborole. AcoR cells were hypersensitive to pentamidine and diminazene. All drug sensitivity assays were carried out in duplicate and EC50 values were obtained from at least 3 independent experiments.
Generation of an acoziborole-resistant cell line and analysis of cross-resistance.
A) Acoziborole resistance was generated in T. brucei Lister 427 cells through the addition of incremental concentrations of the benzoxaborole to cell cultures in vitro. Red line indicates mean wild-type EC50 for acoziborole. B) Cell density of the four AcoR clones, as well as a wild-type control, were monitored daily. AcoR cells were grown in the presence of 4.96 μM acoziborole and all cell cultures were passaged (seeding density of 2 × 104 cells/mL) when density reached 2 × 106 cells/mL. Cumulative cell density over a period of 5 days (120 hours) is shown (n = 3 per sample group). C) The AcoR line showed a significantly increased EC50 compared to wild-type cells. Mean EC50 was 4.88 ± 0.56 μM, approximately 25-fold higher than WT cells (EC50: 0.25 ± 0.01). Interestingly, AcoR cells also showed an increased resistance to the AdoMet-dependent MTase inhibitor sinefungin, which was shown to act in similar fashion to acoziborole. AcoR cells were hypersensitive to pentamidine and diminazene. All drug sensitivity assays were carried out in duplicate and EC50 values were obtained from at least 3 independent experiments.To confirm increased resistance against the benzoxaborole, alamar blue assays were carried out in order to generate EC50 values. The AcoR line exhibited a 15-20-fold increase in EC50 to acozibrole (p = 0.0012), compared to wild-type cells (Fig 1C). Several other compounds were tested to check for cross-resistance or cross-sensitivity (Fig 1C). AcoR exhibited a 3.5-fold increase in EC50 against sinefungin, an adenosine analogue that acts as a methyltransferase inhibitor (Fig 1C). We previously observed antagonism between sinefungin and acoziborole, and sinefungin treatment results in similar metabolic phenotypes to those observed in acoziborole-treated cells [35], suggesting they impact upon similar metabolic processes. In contrast, the AcoR line exhibited increased sensitivity to both pentamidine and diminazene aceturate (Fig 1C), both of which are thought to act on the trypanosome mitochondrion [24].To test the stability of the AcoR line, two clones were further analysed (S1 Fig). Resistant cells were grown in the presence or absence of the benzoxaborole (4.96 μM) for 14 days, after which further drug sensitivity assays were carried out with acoziborole (S1 Fig). Interestingly, whilst still mildly, yet significantly (p = 0.0038 and 0.0031 for clones 1 and 2, respectively) resistant (~3-fold increase in EC50), the resistance phenotype appeared to be reversible in AcoR cells when cultured in the absence of acoziborole (S1 Fig). In addition, AcoR cells passaged in the absence of drug exhibited an increased growth rate, compared to cells maintained under drug pressure (S1 Fig).Slow growth of cells is likely to reduce the requirement for RNA processing, which could generate drug resistance in the cases of acoziborole and sinefungin. We therefore examined whether reduction in growth rate, brought about through changes in incubation temperature, could impact on acoziborole sensitivity in wild-type cells (S2 Fig). Cells were maintained in 5% CO2 with lowered temperatures. Whilst a reduction to 34°C did not significantly affect growth rate (doubling times of 7 h and 6.8 h at 37°C and 34°C, respectively), growth was decreased at 30°C (doubling time of 18.5 h). At both temperatures, acoziborole EC50 was significantly reduced (fold changes of 1.95 and 3.02 for 37°C vs. 34°C and 37°C vs. 30°C, respectively) compared to 37°C controls (S2B Fig), indicating increased acoziborole sensitivity.
AcoR line exhibits a ‘stumpy’ or ‘procyclic’ transcriptome
To characterise the AcoR cell line, and dissect the changes in expression that rendering the parasite drug-resistant, RNA-sequencing was carried out on all four AcoR clones as well as the parental wild-type Lister 427 and a wild-type passage control cultured in the absence of acoziborole. Reads (mean number of reads: 11,815,635 ± 1,128,622) were aligned to a ‘hybrid’ genome consisting of 11 core chromosomes from the TREU 927 reference genome complemented by BES contigs from the Lister 427 genome (mean alignment rate: 83.52 ± 0.33%). The resulting alignment files were filtered for primary alignments only (Samtools), before read counts for each gene were calculated (HTseq). Finally, differential expression (DESeq2) as well as polymorphisms (SnpEff) were analysed (see Materials and Methods for details).The final differential expression dataset consisted of 10,151 genes (after removing genes with read counts of <10). Significant changes in transcript abundance were observed for 4,061 genes based on Padj (P-value adjusted by Benjamini-Hochberg correction) alone, although this was reduced to 796 genes when taking into account a Log2 fold change of ≥ 1 or ≤ -1 (Fig 2 and S1 Table). Of these, 178 transcripts were significantly increased in abundance, whilst the remaining 618 genes were significantly decreased (Fig 2A and S1 Table).
Fig 2
Overview of transcriptomics analysis of the AcoR cell line.
A) Volcano plot of statistical significance (Padj < 0.05) against fold change (Log2 fold change <-1 or >1) between AcoR and wild-type cells. Differentiation expression was calculated using DESeq2 [66]. Transcripts undergoing significant differential expression based on the aforementioned parameters are highlighted in red. B) Volcano plot of the same RNAseq data highlighting changes in expression of life-cycle stage-specific surface proteins. Green data points are genes whose production descriptions match “VSG”, whilst purple points indicate BSF-associated expression sites (ESAGs). Finally, red data points indicate genes whose annotation include “procyclin”, which includes GPEET and EP procyclin. C) Data from this study was compared to previously published transcriptomics data comparing stumpy (ST) form to slender (SL) form T. brucei [13]. Raw data from the Silvester et al. study [13] was processed by the same means as the data generated here (AcoR vs wild-type; WT), and log2 fold change (as calculated by DESeq2) of AcoR/WT was compared to ST/SL by linear regression (R2; blue dotted line) and correlation (Pearson’s r).
Overview of transcriptomics analysis of the AcoR cell line.
A) Volcano plot of statistical significance (Padj < 0.05) against fold change (Log2 fold change <-1 or >1) between AcoR and wild-type cells. Differentiation expression was calculated using DESeq2 [66]. Transcripts undergoing significant differential expression based on the aforementioned parameters are highlighted in red. B) Volcano plot of the same RNAseq data highlighting changes in expression of life-cycle stage-specific surface proteins. Green data points are genes whose production descriptions match “VSG”, whilst purple points indicate BSF-associated expression sites (ESAGs). Finally, red data points indicate genes whose annotation include “procyclin”, which includes GPEET and EP procyclin. C) Data from this study was compared to previously published transcriptomics data comparing stumpy (ST) form to slender (SL) form T. brucei [13]. Raw data from the Silvester et al. study [13] was processed by the same means as the data generated here (AcoR vs wild-type; WT), and log2 fold change (as calculated by DESeq2) of AcoR/WT was compared to ST/SL by linear regression (R2; blue dotted line) and correlation (Pearson’s r).Strikingly, the majority of genes exhibiting increased transcript abundance (Padj ≤ 0.05, Log2 fold change ≥1) in the AcoR line have been previously classified as stumpy-form- or PCF-specific genes. In particular, GPEET and EP procyclins (Tb927.6.510, Tb927.10.10260 and Tb927.10.10250 for GPEET, EP1 and EP2, respectively), both surface markers of early and late-differentiated PCFs, respectively, exhibited elevated transcript abundance (Fig 2B and Table 1). A nucleoside transporter, orthologous to TbNT10, previously reported to be up-regulated in stumpy form parasites, was also elevated on AcoR cells (Tb927.2.6320; Table 1) [44]. Further examples included pyruvate phosphate dikinase (Tb927.11.6280) and transketolase (Tb927.8.6170), previously shown to be expressed exclusively in PCF T. brucei (S1 Table) [45,46], and a single strand-specific nuclease, reported to be up-regulated in differentiating trypanosomes (Tb927.6.2890) [47]. Finally, abundances of transcripts encoding PAD proteins, as well as PIP-39 (Tb927.9.6090), known to be involved in BSF-to-stumpy differentiation, were also increased in the AcoR cell line (Tables 1 and S1).
Table 1
Top 20 genes with significantly increased abundance in AcoR cells.
Only one example shown for repeated genes. For full results see S1 Table.
Top 20 genes with significantly increased abundance in AcoR cells.
Only one example shown for repeated genes. For full results see S1 Table.There was also increased abundance in transcripts associated with several transporters, such as AATP11 (Tb927.4.4730; S1 Table), three copies of a pteridine transporter (Tb927.1.2820, Tb927.1.2850 and Tb927.1.28; S1 Table) and three nucleoside transporters (TbNT8.1, TbNT8.2 and TbNT10, Tb927.11.3610, Tb927.11.3620 and Tb927.9.7470, respectively; S1 Table).Conversely, transcripts specific to BSF-stage parasites exhibited decreased transcript abundance in the AcoR cell line (Table 2). In particular, there was widespread downregulation of VSGs and expression site associated genes (ESAGs; Fig 2B). Whilst trypanosomatids typically express only one VSG and an associated expression site at any one time, the appearance of numerous VSGs in the transcriptomics dataset are likely the result of short paired-end reads aligning to multiple annotated VSGs that exhibit close homology. Importantly, the predominant VSG in Lister 427, VSG221 (Tb427.BES40.22), was also significantly reduced (Log2 fold change: -1.62, Padj = 0.003; S1 Table). Furthermore, glucose transporters, several adenosine and nucleoside transporters, and glycolytic components such as pyruvate kinase 1 (Tb927.10.14140; S1 Table), a pyruvate transporter (PT1, Tb927.3.4070; S1 Table) hexokinase (Tb927.10.2010 and Tb927.10.2020; S1 Table) and glyceraldehyde 3-phosphate dehydrogenase (Tb927.6.4280 and Tb927.6.4300; S1 Table) were all significantly (p < 0.05) reduced in the acoziborole-resistant cells (S1 Table).
Table 2
Top 20 genes with significantly decreased abundance in AcoR cells.
Only one example shown for repeated genes. For full results see S1 Table.
expression site-associated gene 11 (ESAG11), fragment
-2.83
5.28E-03
Top 20 genes with significantly decreased abundance in AcoR cells.
Only one example shown for repeated genes. For full results see S1 Table.No changes in expression were observed in CPSF3 (Tb927.4.1340; S1 Table), the protein target of acoziborole [33]. There were small but significant decreases observed in mRNA encoding CBP1 (Tb927.10.1030, Tb927.10.1040 and Tb927.10.1050; S1 Table). This gene was recently shown to be a determinant of resistance to the veterinary benzoxaborole AN11736. However, acoziborole does not possess the valyl-ester linker that serves as a cleavage site for CBP1 [40], and thus, this result is unlikely to be of biological significance.Sequence polymorphisms were also analysed in the transcriptomics data in order to assess mutations that may be associated with acoziborole resistance. However, none were found associated with genes encoding proteins that are known to be associated with benzoxaborole mode of action or resistance phenotypes in other systems, although the supplementary table (S2 Table) provides the data for future reference as more knowledge about these compounds and their mechanisms come to light.To test how the transcriptomics data compared to that of BSF-to-stumpy differentiation, further analysis was carried out using previously generated data from two studies [13,48]. Firstly, a study comparing ascending (slender) and peak (stumpy) parasitaemias in vivo [13], and secondly a study comparing slender BSFs, stumpy BSFs, as well as early (socially motile) and late (non-socially motile) procyclics [48]. All data were processed as described in the Materials and Methods section. Firstly, log2 fold changes of stumpy vs. slender (from Silvester et al. [13]) were compared to log2 fold changes of AcoR vs. wild-type (Fig 2C; S1 Table). Linear regression (R2 = 0.284) and Pearson’s correlation coefficient (r = 0.533) were calculated, with both showing significant correlation between the datasets (p < 0.0001), indicating that AcoR cells showed a high degree of similarity, albeit at a transcriptome level, to stumpy-form T. brucei. Interestingly, a large portion of genes down-regulated in stumpy form cells, but not in acoziborole-resistant cells, were associated with cell division. For example, histones and cytoskeletal proteins (S1 Table).Furthermore, there was equally strong correlation between the AcoR vs. wild-type log2 fold changes when compared to log2 fold changes of early and late procyclic cells vs. slender cells (r = 0.505 and 0.540 for comparisons to early and late procyclics, respectively; S3 Fig; S1 Table), from Naguleswaran et al. [48]. Taken together, these results indicated that the acoziborole resistant line exhibited similarities on a transcriptomic level to both stumpy and procyclic-form parasites.
Metabolomics analysis of the AcoR cell line
To further probe changes in the AcoR cell line as a result of induced resistance to the benzoxaborole, LC-MS was carried out on cell pellets to compare wild-type T. brucei to two AcoR clones, both in the presence and absence (cultured without drug for 48 hours, or 1 passage) of acoziborole resulting in six sample groups (n = 4). A total of 754 putative metabolites were identified in the resulting dataset, of which 75 were matched to an authentic standard (S3 Table). The data was subsequently Log2 transformed and Z-scaled (Log transformation and auto-scaling in Metaboanalyst, respectively), and one-way ANOVA was applied to identify metabolites whose abundance was significantly changed between the sample groups (S3 Table). This resulted in 197 metabolites identified as significantly altered (False discovery rate, FDR < 0.05; Fig 3A, full ANOVA results in S4 Table).
Fig 3
Metabolomics analysis of AcoR cells.
A) Results of an analysis of variance (ANOVA) on 754 putatively identified metabolites. Each peak was assigned a number (S3 Table) for clarity, and significant metabolites (FDR < 0.05; 197 metabolites) are highlighted in red. B) Heat map of significantly altered metabolites (ANOVA, FDR < 0.05). LC-MS peak intensities were log transformed and auto-scaled (mean-centred, divided by the standard deviation for each metabolite). Both samples and metabolites were clustered, showing clear separation of the wild-type, acoziborole-treated samples from all other sample groups. C) AdoMet metabolism is significantly disrupted during acoziborole treatment in wild-type cells, but unchanged in AcoR cells irrespective of drug treatment. However, acoziborole is still detected in AcoR cell pellets. Abbreviations: Aco, acoziborole; AdoMet, S-adenosyl-L-methionine; 5’-MTA, 5’-methylthioadenosine.
Metabolomics analysis of AcoR cells.
A) Results of an analysis of variance (ANOVA) on 754 putatively identified metabolites. Each peak was assigned a number (S3 Table) for clarity, and significant metabolites (FDR < 0.05; 197 metabolites) are highlighted in red. B) Heat map of significantly altered metabolites (ANOVA, FDR < 0.05). LC-MS peak intensities were log transformed and auto-scaled (mean-centred, divided by the standard deviation for each metabolite). Both samples and metabolites were clustered, showing clear separation of the wild-type, acoziborole-treated samples from all other sample groups. C) AdoMet metabolism is significantly disrupted during acoziborole treatment in wild-type cells, but unchanged in AcoR cells irrespective of drug treatment. However, acoziborole is still detected in AcoR cell pellets. Abbreviations: Aco, acoziborole; AdoMet, S-adenosyl-L-methionine; 5’-MTA, 5’-methylthioadenosine.Clustering of the samples using the 197 significantly altered metabolites showed that acoziborole-treated wild-type cells were most divergent from the other 5 sample groups (Fig 3B), indicating that resistant cells both in the presence and absence of acoziborole exhibited a metabolic phenotype closer to that of wild-type cells than that of drug-treated sensitive cells.The most notable changes involved those in S-adenosyl-L-methionine (AdoMet) metabolism, as previously observed [35] (Fig 3C). In both AcoR clones, both in the presence and absence of acoziborole, the increases in AdoMet, 5’-methylthioadenosine (5’-MTA) and adenine were absent, suggesting resistant parasites were able to withstand the metabolic impact of acoziborole treatment. Adenosine levels were elevated in AcoR samples (S3 Table), corresponding to elevated transcript levels of adenine phosphoribosyltransferase (Tb927.7.1790; S1 Table). Importantly, intracellular acoziborole abundance (determined through finding a peak at the mass of the drug) remained high in AcoR cells, suggesting resistance was not a result of reduced accumulation of the compound across the plasma membrane either through reduced uptake or increased efflux (Fig 3C).Several other putatively identified metabolites followed a similar trend to AdoMet, including 4-hydroxy-4-methlglutamate, mono-, di- and tri-methyl-L-lysine, 5-guanidino-2-oxopentanoate (2-oxoarginine) and 8-amino-7-oxononanoate (S3 Table), the latter thought to be involved in AdoMet-dependent transaminase reactions leading to biotin synthesis. Taken together, these data suggest that the significant metabolic perturbations that were the hallmark of acoziborole treatment in wild-type T. brucei were nullified in resistant cells even though drug uptake appeared to be unaffected. Apart from acoziborole itself, there were no significant differences (t-test, FDR < 0.05) between treated and untreated AcoR cells, highlighting that drug treatment of these resistant cells did not lead to further metabolic perturbations.Several metabolites were altered only in AcoR cells compared to WT T. brucei. The most significant perturbation restricted to AcoR cells only was putatively identified, based on its mass and predicted formula, as nonaprenyl-4-hydroxybenzoate (Fig 4A), a metabolite involved in the synthesis of ubiquinone-9 [49], but not previously reported in T. brucei and a metabolite for which no authentic standard was available to confirm identity. 2-oxoglutarate, a citric acid cycle intermediate, was also increased in AcoR cells (Fig 4B). Interestingly, transcripts associated with key enzymes in oxoglutarate metabolism, such as glutamate dehydrogenase (Tb927.9.5900), and the oxoglutarate dehydrogenase complex (Tb927.11.11680, Tb927.11.9980 and Tb927.11.1450; S1 Table), were all elevated in AcoR cells. Conversely, pyruvate levels were reduced in resistant cells (S3 Table), correlating with reduced pyruvate kinase 1 expression (S1 Table).
Fig 4
Metabolites elevated significantly in AcoR cells.
Metabolomics data was mined to identify metabolites altered in AcoR cells compared to wild-type T. brucei. Metabolites identified as nonaprenyl 4-hydroxybenzoate (A) and 2-oxoglutarate (B) support the indications that the AcoR is in a differentiated state, as they are involved with ubiquinone and citric acid cycle metabolism, respectively. Levels of both L-carnitine (C) and O-acetylcarnitine (D) are reduced in wild-type cells after acoziborole-treatment. However, both were observed at significantly higher levels in AcoR cells both in the presence and absence of acoziborole. Orotate (E) and (S)-dihydroorotate (F) are intermediates of uridine monophosphate and ultimately, uridine triphosphate biosynthesis, which is required for UTP-dependent mitochondrial mRNA polyadenylation. Levels of these metabolites are similarly reduced in acoziborole-treated wild-type cells, but elevated in AcoR cells. Abbreviations: Aco, acoziborole.
Metabolites elevated significantly in AcoR cells.
Metabolomics data was mined to identify metabolites altered in AcoR cells compared to wild-type T. brucei. Metabolites identified as nonaprenyl 4-hydroxybenzoate (A) and 2-oxoglutarate (B) support the indications that the AcoR is in a differentiated state, as they are involved with ubiquinone and citric acid cycle metabolism, respectively. Levels of both L-carnitine (C) and O-acetylcarnitine (D) are reduced in wild-type cells after acoziborole-treatment. However, both were observed at significantly higher levels in AcoR cells both in the presence and absence of acoziborole. Orotate (E) and (S)-dihydroorotate (F) are intermediates of uridine monophosphate and ultimately, uridine triphosphate biosynthesis, which is required for UTP-dependent mitochondrial mRNA polyadenylation. Levels of these metabolites are similarly reduced in acoziborole-treated wild-type cells, but elevated in AcoR cells. Abbreviations: Aco, acoziborole.Levels of L-carnitine and O-acetylcarnitine (Fig 4C and 4D, respectively) were both elevated (the latter only significantly elevated in untreated AcoR cells). However, there were no significant transcript changes observed in genes encoding proteins involved in carnitine metabolism, such as carnitine O-acetyltransferase (Tb927.11.2230; S1 Table). One previous study suggested that intracellular carnitine levels in PCF cells are higher than those in BSF cells [50] and therefore, elevated carnitine levels could be the result of increased influx. There were also increases in orotate and (S)-dihydroorotate in the AcoR line (Fig 4E and 4F, respectively), both precursors of UMP biosynthesis, although a peak corresponding to UMP was not detected, likely due to technical limitations of the mass spectrometer. No transcript changes were detected for genes directly involved in the synthesis of orotate and (S)-dihydroorotate, although significant reductions were exhibited in several genes involved in pyrimidine metabolism (nucleoside diphosphatase, Tb927.7.1930, Log2 fold change = -1.80; uridine phosphorylase, Tb927.8.4430, -1.47; nucleoside hydrolase, Tb11.v5.0270, -1.02; S1 Table). Finally, AcoR cells had significantly (FDR = 0.0021; S4 Table) reduced levels of L-cystathionine (S3 Table)Comparison of untreated wild-type cells with untreated AcoR cells by FDR corrected t-test (FDR < 0.05) showed a total of 52 significantly altered metabolites, the majority of which were identified in the ANOVA analysis outlined above. The statistical outputs are provided in S4 Table.Metabolomics data were also compared to that of acoziborole-treated PCF cells [35]. Most metabolic changes occurring in wild-type BSF T. brucei after acoziborole treatment also occurred in PCF cells, albeit with a significantly higher drug dose, reflective of the higher dose required to kill PCF trypanosomes [35]. However, there were key differences, some of which were also observed in AcoR cells. For example, a peak putatively identified as 4-hydroxy-4-methylglutamate (a component of C5-branched dibasic acid metabolism) was increased upon acoziborole treatment in BSF T. brucei, but reduced in both AcoR and PCF. PCF trypanosomes also exhibit less significant increases in adenine compared to BSF after acoziborole treatment [35], similar to AcoR cells. Finally, there was reduced perturbation in other pyrimidines such as cytidine and deoxyuridine in both PCF and AcoR cells, both of which are reduced in BSF parasites post-treatment (S3 Table). However, because the PCF experiments were carried out independent of this study, it is difficult to directly compare metabolite abundances.
AcoR cells retain BSF morphology
The morphology of T. brucei differs significantly depending on life cycle stage. BSFs are long and slender, whilst stumpy-forms are rounded and short, as their name implies. In contrast, PCFs are elongated and exhibit decreased distance between kinetoplast (mitochondrial DNA) and nucleus [51].Given the “stumpy”- or “procyclic”-like profile observed on both transcriptome and metabolome levels, we analysed AcoR cell morphology (Fig 5), to determine whether the PCF-like phenotype was also reflected in cell shape and size, as well as organelle arrangement. Overall morphology appeared to resemble that of classical BSF T. brucei (Fig 5A). In addition, mitochondrial arrangement was no different to that of wild-type BSF T. brucei (Fig 5A). In this life cycle stage, the mitochondrion remains metabolically inactive, and is present as a single tube stretching throughout the cell. Although the localisation of the nucleus and kinetoplast, the organelle containing mitochondrial DNA, appeared to be normal in AcoR lines, the distance between the two was further analysed in both wild-type and AcoR cells (Fig 5B). A small, but significant (Student’s T-test, P < 0.0001) difference in nucleus-kinetoplast distance was present, suggesting that the nucleus and kinetoplast localise closer together in the AcoR cell line.
Fig 5
Microscopy analysis of AcoR cells.
A) Morphology and organelle arrangement in AcoR cells was analysed by fluorescence microscopy. Overall morphology appeared to be similar to typical BSF parasites (differential interference contrast; DIC). In addition, kinetoplast DNA was localised to the posterior end of the cell (DAPI). Finally, localisation and shape of the single mitochondrion was observed to be normal (Mitotracker red; MT-RED). Scale bar represents 5 μm. B) The distance between the centre of the nucleus and kinetoplast were measured (n = 100, 3 independent samples) in wild-type and AcoR cells. Results were analysed for significance by applying an unpaired t-test (****p < 0.0001).
Microscopy analysis of AcoR cells.
A) Morphology and organelle arrangement in AcoR cells was analysed by fluorescence microscopy. Overall morphology appeared to be similar to typical BSF parasites (differential interference contrast; DIC). In addition, kinetoplast DNA was localised to the posterior end of the cell (DAPI). Finally, localisation and shape of the single mitochondrion was observed to be normal (Mitotracker red; MT-RED). Scale bar represents 5 μm. B) The distance between the centre of the nucleus and kinetoplast were measured (n = 100, 3 independent samples) in wild-type and AcoR cells. Results were analysed for significance by applying an unpaired t-test (****p < 0.0001).
Discussion
Subspecies of the protozoan parasite Trypanosoma brucei are the causative agents of HAT, a debilitating disease prevalent across the sub-Saharan African continent. Whilst case numbers continue to decline, there is an urgent need for safe, effective and orally bioavailable chemotherapeutics if the target of elimination is to remain feasible.Acoziborole is a novel trypanocide currently in clinical trials and has shown great potential as a front line drug to combat both early- and late-stage HAT caused by both T. b. gambiense and T. b. rhodesiense. The drug is effective in a single dosing, representing a truly remarkable step change in possible therapy of HAT. While a mode of action of acoziborole and a related veterinary benzoxaborole, and their protein target, CPSF3, were recently identified [32,33], less is known about potential parasite mechanisms of resistance against the compound. One study, however, did reveal that one of several genomic changes was an increase in copy number of the CPSF3 gene, pointing to a potential mechanism where increased target concentration causes a proportional resistance to the drug [39]. We attempted to ascertain whether expression or sequence of CPSF3 (Tb927.4.1340), varied compared to wild-type. However, no altered expression nor sequence was observed in this gene in our resistant line. Unfortunately, in the absence of data other than transcript abundance we cannot definitively exclude a role for CPSF3.This study outlines the characterisation of a laboratory-derived acoziborole-resistant T. brucei cell line using omics-based technologies. The AcoR line exhibited high levels of acoziborole resistance and interestingly, cross-resistance to sinefungin, an AdoMet-dependent methyltransferase inhibitor. We previously found similarities between the metabolic phenotypes of acoziborole- and sinefungin-treated cells [35]. In addition, when used simultaneously, the interaction appears to be antagonistic, suggesting inhibition of similar biological processes, in this case, mRNA maturation. AcoR cells also exhibited hypersensitisation against pentamidine and diminazene. Uptake of the latter is known to be mediated by the TbAT1 transporter (or P2; Tb927.5.286b), although transcripts associated with this gene were down-regulated in the resistant cells (S1 Table). Pentamidine also enters via TbAT1, but there is also major uptake via the Aquaglyceroporin 2 (AQP2) transporter, although transcript abundance of this gene (Tb927.10.14170) remained unchanged in acoziborole resistant cells. Thus, hypersensitisation to diamidines would appear to be unrelated to transcript levels of the genes encoding the key transporters of these compounds.Remarkably, transcriptomics analysis of the resistant line suggests that the parasites underwent a “partial differentiation event” in acquiring acoziborole resistance. This is emphasized by increased abundance of transcripts associated with stumpy and procyclic forms, such as EP/GPEET procyclins and PTP-1, as well as upregulation of several PCF-specific metabolic genes such as transketolase and pyruvate phosphate dikinase, the latter not expressed in BSF T. brucei [45,46,52]. Transcripts associated with proteins involved in stage-specific regulation of mRNA (e.g. increases in PAD1, PAD2, ZC3H11 and ZC3H22; Tb927.7.5930, Tb927.7.5940, Tb927.5.810 and Tb927.7.2680, respectively) were also significantly altered. Concomitantly, AcoR cells exhibited reduced abundance of BSF-stage transcripts such as VSG and the THT-1 glucose transporters. Given the apparent loss of variant surface glycoproteins and ESAGs, known to be essential to successful growth in mammalian blood [53,54], we did not test the ability of these cells to survive in mammals where we would presume them to be unviable.A significant limitation in this study is the lack of protein level data to complement the transcriptional data outlined here. We have assumed that transcription acts as a proxy for the cellular proteome, but additional work, such as proteomics or transmission electron microscopy is required to verify this.Interestingly, in the context of the data outlined here, Jones and colleagues found genomic deletions in one resistant cell line in a region corresponding to the AdoMet decarboxylase (AdoMetDC) array [39], but we could not identify similar alterations in the AcoR line. There was, however, a small but significant reduction in transcript abundance of a tRNA-methyltransferase (Tb927.6.4420, S1 Table). This gene underwent a deletion in acoziborole-resistant cells generated in the aforementioned study [39].Recent studies in T. brucei have highlighted similarities between the pathways controlling differentiation and those controlling stress responses [55,56]. Furthermore, treatment with suramin, a frontline drug for the management HAT, was recently shown to lead to an increase in mitochondrial ATP production and expression of proteins normally associated with PCF trypanosome metabolism [57]. Further work must be carried out, including on a proteomic level, to determine whether the stumpy/PCF phenotype resulting from generation of resistance to acoziborole is a direct response to benzoxaborole action, or a conserved global response to drug pressure or other pressures. Our data indicate that removing drug pressure reverses the resistance phenotype significantly, and this is coupled to increased growth rate. However, our data suggests that induction of stress by reduction of temperature, which is also coupled to reduced growth rate, is not sufficient to generate acoziborole resistance and thus, there remain unidentified mechanisms involved in generating resistance to this compound.Notably, this study used the Lister 427 T. brucei cell line, which is known to be monomorphic and carries defects in the classical trypanosome differentiation pathway [42]. Drug resistance in African trypanosomes typically arises through the loss of drug-uptake transporters [22,58], increased drug efflux [59], or overexpression of the drug target [33], and the resistance phenotype uncovered in this study was unexpected. Given these data, it would be worthwhile to further investigate acoziborole resistance in pleiomorphic T. brucei to test whether the acoziborole resistance mechanism described here can also occur in normally differentiation competent cells.Although we have not identified the specific mechanism of resistance, the work we report here has demonstrated that a global switch in transcriptome from a typical BSF type to a stumpy/PCF-like type can accompany selection of resistance in T. brucei. Procyclic forms are less susceptible to acoziborole than BSF (EC50: ~0.2 μM and ~1.5 μM for BSF and PCF, respectively; [35]), hence some distinguishing aspect of PCF physiology might underlie the change in sensitivity and a change of transcription profile could be sufficient to select for resistance. The fact that the CPSF3 target is necessary for both BSF and PCF parasites could indicate the presence of other, as yet unidentified targets for acoziborole in T. brucei, pointing to a degree of polypharmacology associated with benzoxaboroles. The mechanism of global transcriptional change is unlikely to be relevant to selection of resistance to these drugs in clinical practice as the parasites require a VSG coat that would appear to be lost (albeit, at the transcriptome level) in the process and also have biochemical adaptations essential to living in the bloodstream that differ from those required for PCF to live in the tsetse fly midgut.
Materials and methods
T. brucei in vitro culture and generation of acoziborole resistance
Bloodstream form (BSF) T. brucei culture was carried out using the 427 Lister strain [43]. Cells were cultured in HMI-11 (supplemented with 10% foetal bovine serum) and maintained at 37°C, 5% CO2. Cultures were maintained at densities of 2 × 104–2 × 106 cells/mL. In vitro resistance to acoziborole was initiated by maintaining cells in 170 nM of the compound, which was deemed the highest concentration wild-type cells could tolerate long term. Once a cell line was established in this concentration, cells were then transferred to 6 wells of a 24-well plate at a density of 1 × 105 cells/mL. Six incrementing concentrations of acoziborole were then added, to obtain six 2 mL cultures. Typically, increments of 0.2 μM were used, and cells were incubated at 37°C and 5% CO2. Cells were routinely observed by microscopy and after >2 weeks, live confluent cells in the highest concentration of acoziborole were cultured for 2 passages in the same concentration of the benzoxaborole, before transfer to 6 new wells in a 24-well plate, from which point the process was repeated using the new acoziborole concentration as a starting point. A wild-type cell line was grown in the absence of drug as a “highly-passaged” control, in order to detect transcriptome changes related to in vitro culture adaptation. Once sufficient resistance was deemed to have been generated, cells were cloned by dilution and 4 isolates were recovered.For quantitative growth analysis, cultures were maintained at the densities described above. Growth curves were plotted cumulatively, by taking the dilution factor after passage into account. Growth rates were calculated using the exponential (Malthusian) growth model algorithm in GraphPad Prism (v8.4.0; www.graphpad.com).
Alamar blue assays
To obtain in vitro EC50 values for specific compounds targeting T. brucei, alamar blue assays were employed (adapted from [60]). This colorimetric assay was carried out in solid white flat-bottomed 96-well plates. Compounds were added starting with the highest concentration (typically 100 μM) and serially diluted 1:2 over 23 wells, leaving one negative control. Subsequently, cells were added at a final density of 2 × 104 cells/mL. Plates were incubated for 48 hours at 37°C, 5% CO2, after which 20 μL of alamar blue reagent (resazurin sodium salt, 0.49 mM in 1× PBS, pH 7.4) was added to each well, and the plate incubated for a further 24 hours. In experiments involving the AcoR cell line, the incubation time after addition of alamar blue was 48 hours for all sample groups.Reduction of the alamar blue reagent was measured as a function of cell viability on a BMG FLUOstar OPTIMA microplate reader (BMG Labtech GmbH, Germany) with λexcitation = 544 nm and λemission = 590 nm. The raw values were plotted against the log value of each concentration of drug or compound (M), and EC50 values were calculated using a non-linear sigmoidal dose-response curve. Each assay was performed in duplicate, and EC50 values represent a mean of three independent experiments.
Transcriptomics & data analysis
Total RNA was extracted from in vitro cultures of 108 cells. RNA was purified using a commercial kit (Nucleospin RNA, Macherey-Nagel). A DNase treatment step was included in the kit protocol. RNAseq was carried out by Glasgow Polyomics. The RNA library was prepared using PolyA selection using the TruSeq stranded mRNA sample prep kit (Illumina) and sequencing was carried out using Illumina NextSeq500 sequencing apparatus.Sequencing files were processed as follows: Raw reads were trimmed and read quality and coverage was assessed using FastQC [61]. Once all sequencing data was judged to be of good quality, the reads were aligned to a hybrid genome consisting of TREU 927 (TriTrypDB; v50.0) core chromosomes complemented with Lister 427 (TriTrypDB; v50.0) BES contigs using HiSat2 (parameters:—no-spliced-alignment) [62,63]. Further filtering and removal of duplicates was done using Samtools (parameters for samtools view: -bS–q 1; parameters for samtools sort: -O BAM) [64]. To analyse differential expression, reads were first counted using htseq-count (parameters: -s reverse -f bam -t exon -i Parent -m union—non-unique-all), part of the HTSeq python library [65], before analysis of expression with DESeq2 [66]. For SNP and indel analysis, raw data was aligned to the Lister 427 genome (427 2018, v50.0) as described above, and data was further processed using the genome analysis tool-kit (GATK) [67]. SNPs and indels were filtered using the SnpEff/SnpSift package [68]. RNAseq data is available at GEO (Accession number: GSE168394).
Metabolomics, LC-MS & data analysis
Samples for metabolomics analysis were acquired by rapidly quenching 8 × 107 cells in log phase in a dry-ice/ethanol bath, to ~4°C. For each sample group, four replicates were grown independently. After quenching, samples were centrifuged for 10 minutes at 1,500 × g, 4°C, and all experimental steps hereafter were carried out at 4°C. Supernatant was poured off and cells resuspended in the remaining supernatant. Samples were then transferred to a 1.5 mL eppendorf tube prior to another centrifugation step at 1,500 × g for 5 minutes. Remaining supernatant was carefully removed, and the cells resuspended in 200 μL extraction solvent. All samples, including a blank and fresh medium control, were then left on a shaker at 4°C for one hour. Subsequently, samples were centrifuged at 16,060 × g for 10 minutes, and the supernatant was transferred to a 2 mL screw-top tube. A quality control sample was generated by pooling together 10 μL from each sample. Finally, air was displaced with argon gas, and samples were stored at -80°C until they were analysed by liquid chromatograph-mass spectrometry.Liquid chromatography-mass spectrometry was carried out by Glasgow Polyomics. Metabolomics samples were separated by HPLC using a ZIC-pHILIC (polymer-based hydrophilic interaction liquid chromatography) column (Merck). Two solvents were used in the column. Solvent A was 20 mM ammonium carbonate in H2O and solvent B was 100% acetonitrile. Mass detection was carried out using an Exactive Orbitrap mass spectrometer (Thermo). The mass spectrometer was run in positive and negative mode with an injection volume of 10 μL and a flow rate of 100 μL/minute.Raw mass spectrometry data was converted to mzXML format and split into positive and negative polarity using msconvert [69]. Files were then converted to peakML files with XCMS, which were further processed using mzMatch [70] and Ideom [71]. Data analysis was carried out using Ideom and Metaboanalyst [72]. Data is available at Metabolights (Accession number: MTBLS2559).
Preparation of slides & microscopy
Mitochondria were stained using Mitotracker Red (Invitrogen) prior to fixation and mounting. Cells (1 mL at a density of 5 × 105 cells/mL) were incubated for 5 minutes at 37°C, 5% CO2, with a final concentration of 100 nM Mitotracker. Cells were subsequently centrifuged for 5 minutes at 1,500 × g and washed twice in fresh medium before fixation by addition of a final concentration of 2% formaldehyde in PBS, and a 15-minute incubation at room temperature. Samples were then washed with PBS and transferred onto a poly-L-lysine-coated slide, which was left to air-dry in a biological safety cabinet. Dried slides were rehydrated and washed in PBS, and a counterstain consisting of 1× PBS with 3 μM 4,6-diamidino-2-phenylindole (DAPI) was applied to the slide, before mounting with a coverslip that was sealed with clear nail varnish. Slides were analysed with a Zeiss axioscope (Scope.A1, Zeiss).To measure the distance between nucleus and kinetoplast, images were obtained from DAPI stained samples and these imported into the Fiji software [73]. Distances were measured after the scale was set using the “measure” tool. For each sample group, 100 measurements were taken in total from three independent microscopy experiments (30–40 measurements per sample group).
Computational methods
Graphical representation of data was generated using the Graphpad Prism software (v8.4.0; www.graphpad.com) or R [74]. Statistical analyses were carried out using Graphpad Prism, Microsoft Excel or R.
Analysis of reversibility of acoziborole-resistance.
Two clones of the AcoR line were grown for 14 days in the presence (+Aco) or absence (-Aco) of 4.96 μM acoziborole, prior to testing sensitivity to the benzoxaborole, compared to a wild-type (WT) control. A) Sigmoidal dose-response curves of two clones in the presence or absence of acoziborole with a wild-type control. A shift to the right indicates increased acoziborole resistance. B) Mean EC50s from three independent experiments. Acoziborole resistance is reversed in AcoR cells grown without drug pressure, although resistance is still significant compared to that of wild-type cells (Student’s T-test, **p < 0.01, ****p < 0.0001). C) Cumulative growth curves of wild-type T. brucei and AcoR cells in the presence or absence of 4.96 μM acoziborole. Mean doubling times were 7.6 h, 10.8 h, 12.7 h, 7.1 h and 6.8 h for WT, clone 1 +Aco, clone 2 +Aco, clone 1 -Aco and clone 2 -Aco, respectively.(TIFF)Click here for additional data file.
Acoziborole sensitivity under temperature-induced slow growth conditions.
Wild-type T. brucei was grown at lower temperature (34°C and 30°C) to test the effect of reduced growth rate on acoziborole sensitivity. A) Growth was significantly reduced at 30°C (doubling times: 7.0 h, 6.8 h and 18.5 h at 37°C, 34°C and 30°C, respectively, calculated using an Malthusian growth model) only. B) Acoziborole sensitivity was significantly increased in T. brucei when cultured under conditions of lower temperature and reduced growth rate. Statistics performed by unpaired t-test, **p < 0.01.(TIFF)Click here for additional data file.
Comparative RNAseq analysis of AcoR cells with stumpy and procyclic cells.
Transcriptomics data generated by Naguleswaran and colleagues [48] was processed by the same means as the data generated in this study and log2 fold changes (as calculated by DESeq2) of AcoR vs. WT were compared to log2 fold changes of stumpy vs. slender (A), early procyclic vs. slender (B) and late procyclic vs. slender (C). In this study, early procyclics showed coordinated social motility whilst late procyclics did not [48]. Significance of correlations between the datasets were tested by linear regression (R2; blue dotted line) and Pearson correlation (Pearson’s r). Abbreviations: St: stumpy; Sl: slender; Ea: early procyclic; La: late procyclic.(TIFF)Click here for additional data file.
Excel file containing differential gene expression analysis comparing the acoziborole-resistant cell line to wild-type T. brucei as output by DESeq2.
The dataset is divided into 4 worksheets. The first contains DESeq2 output from the AcoR cell line analysis; the second contains HTSeq-count output for each sample used in this study. The final two worksheets contain the comparisons of the DESeq2 output from this study to previously published comparisons of slender BSF vs. stumpy form [13], and slender BSF vs. PCFs [48]. These worksheets also contain columns with calculated distance from an “X = Y” line for each gene, in both comparisons. Hypothetically, if log2 fold change for a gene in the AcoR/WT comparison was equal to that from the other comparisons, the gene would fall on an X = Y line when plotted on a scatter plot. These columns are the calculated deviation from this line for each gene. Positive values indicate a higher log2 fold change in the AcoR/WT dataset, and conversely, negative values indicate a lower log2 fold change in the AcoR/WT dataset, when compared to the aforementioned data.(XLSX)Click here for additional data file.
Excel file containing SNP and indel analysis of the AcoR cell line.
The dataset was generated using the SnpEff tool.(XLSX)Click here for additional data file.
Excel file containing results of metabolomics analysis of the AcoR cell line (Ideom output).
(XLSX)Click here for additional data file.
Excel file containing outputs of the statistical analyses of the metabolomics data.
(XLSX)Click here for additional data file.23 Apr 2021Dear Prof. Barrett,Thank you very much for submitting your manuscript "Transcriptional differentiation of Trypanosoma brucei during in vitro acquisition of resistance to acoziborole" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers.All three feel the work is important and of interest to the field but they raise a number of important issues that need to be addressed in a revised manuscript before we can make a decision about acceptance.In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.When you are ready to resubmit, please upload the following:[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).Important additional instructions are given below your reviewer comments.Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.Sincerely,Margaret A Phillips, Ph.D.Deputy EditorPLOS Neglected Tropical DiseasesMargaret PhillipsDeputy EditorPLOS Neglected Tropical Diseases***********************Your manuscript has been reviewed by three experts in the field. All three feel the work is important and of interest to the field but they raise a number of important issues that need to be addressed in a revised manuscript before we can make a decision about acceptance.Reviewer's Responses to QuestionsKey Review Criteria Required for Acceptance?As you describe the new analyses required for acceptance, please consider the following:Methods-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?-Is the study design appropriate to address the stated objectives?-Is the population clearly described and appropriate for the hypothesis being tested?-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?-Were correct statistical analysis used to support conclusions?-Are there concerns about ethical or regulatory requirements being met?Reviewer #1: The methods are appropriate but more extensive analysis is needed for the transcriptome and genome, using the well-annotated TREU927 genome as a basis.Reviewer #2: Yes to all questions asked except for the question about ethical/regulatory concerns where the answer is no. In the summary and general comments my concerns are raised - most can be addressed by the authors without further experiments but there are straightforward immunoblotting or classic TEM analysis for the authors to consider and which would lift the work.Reviewer #3: The objective of the study was to examine possible mechanism of acoziborole resistnace in Trypanosoma brucei through the in vitro generation of resistant lines. The study design is appropriate and the trypanosome strain chosen is the one that is mosyt often used for these kinds of in vitro analyses. There is one issue with the trypanosome strain used and that is that the Lister 427 line is monomorphic and has some defects in the normal trypanosome differentiation pathway, and since the mechanism of resistance uncovered in this study appears to involve a differentiation-type switch in gene expression it would have been useful to use a pleiomorphic line as well. However the existence of this mechanism couldn't have been predicted at the start of the study and so the strain used was appropriate given the more likely mechanisms of resistance (these being drug efflux or overexression of the protein target). It may be the monomorphic nature of the strain used that ensured there was no morphological change to accompany the transcriptomic changes.Sample sizes and statistics are fine.There are no ethical or regulatory issues involved.--------------------Results-Does the analysis presented match the analysis plan?-Are the results clearly and completely presented?-Are the figures (Tables, Images) of sufficient quality for clarity?Reviewer #1: Benzoxaboroles are likely to be decisive tools in the future control of African trypanosome diseases. The primary target of the drugs that are currently in late-stage trials is the cleavage and polyadenylation factor CPSF3, but various aspects of the drug effects remain unexplained- notably, changes in methylated metabolites. Resistance is always a potential problem for chemotherapy, but for the human candidate, acoziborole, no lines with more than low-level resistance have been described. In this paper, the authors describe T. brucei that are roughly 20-fold resistant to acoziborole. They show changes in methylated metabolites, with no further effects upon treatment. Although the mechanism is-as before, completely unknown, the results do hint at some polypharmacology which may contribute to the severe difficulty in obtaining resistance. The resistant cells also grow very slowly, which would almost certainly preclude selection in the field. However the slow growth could also be the reason why the cells tolerate the drug.The authors claim that the cells are procyclic-like in their transcriptomes but actually they don't know because they have not done a quantitative comparison with procyclic- or stumpy-form transcriptomes. From the growth kinetics, morphology and transcriptome results, I suspect that these cells are actually showing some characteristics of stumpy-form trypanosomes, more than procyclics.Major modifications required: The sequencing alignment was done with the most recent genome of the cognate strain, Lister427. While this is essential for examining VSG expression sites, it is pretty useless for everything else. This is because the annotation of that genome is really poor. It is impossible to tell, from these Tables, what gene products are actually affected. More importantly, it is not possible compare the transcriptome results presented here with any of those previously published. It is therefore essential to supply equivalent tables made using the TREU927 genome annotation, which is way superior for everything except expression sites. From my own experience, I can say that it will be essential to re-do the sequence alignments, because the Tables of homologues that can be downloaded from TritrypDB are incomplete. One table (or sheet) should include raw read counts so that it is possible for others to do quantitative comparisons without repeating the alignments. Please include both the open reading frames and the 3'-UTRs; this will enable genes with similar ORFs, but different regulation (such as PGKB and PGKC) to be distinguished. The authors must also then do a comparison with published stumpy-form and procyclic-form transcriptomes, to see which most closely resembles the resistant cells; and also look at cell-cycle regulation. It is indeed revealing that in the discussion, the authors revert to the 927 numbers - referring the reader to supplementary Tables on which these numbers cannot be found! In fact in Table S1 the authors do not even show the 427 gene IDs of the increased and decreased transcripts.Exactly the same applies to the SNP and indel analysis. You can't tell if something is important if you don't know the gene function. The whole analysis also needs to be done again using 927. You can check afterwards whether the changes are simply differences between 427 and 927.Table 1: Please compress this to include only one example of the repeated genes. Simplify the annotations (not just copy-paste of the database entry) and show GeneDB numbers for the homologues (if present) in TREU927. The RHS proteins are known to have various different functions: which ones are affected here? Which nucleoside transporter is it, most are now characterised? For example, Tb427_000257300.1 turns out to most likely be an ESAG3 pseudogene, but I had to blast the nucleotide sequence onto 927 to find out. What are all the other "hypothetical proteins" in the Table? Aligning to 927 may well tell you. The results would also appear to suggest a decrease in expression site transcription. Please show a screen shot of the read alignment across the active expression site, then it will be possible to tell.Tables in text: Put all Padj values in the same format. Tables everywhere: These results are not accurate to 9 significant figures, please remove superfluous decimal places, it makes the Tables much smaller and much easier to read.Reviewer #2: Yes, but some revision of Fig 1 is needed and revision of Table 2 highly encouraged - see 'Summary and General Comments'Reviewer #3: Most of the results are clearly presented, there are a couple of minor issues:Lines 424-426 Fig 1. Legend to part B does not refer to the figure but talks about changes in EC50 whereas the figure is about doubling times. Also the doubling times should be given quantitatively as numbers rather than just showing growth curves (Lines 122-123)Line 426 The C is missing where the legend should refer to part C.Fig 5A - surely tha authors could have got a better image of a single cell rather than one that is folded back on itself.--------------------Conclusions-Are the conclusions supported by the data presented?-Are the limitations of analysis clearly described?-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?-Is public health relevance addressed?Reviewer #1: It seems very likely that the cells are acoziborole resistant because they are growing very slowly. Slow-growing parasites have a lower requirement for RNA processing than normal cells. This could also explain the resistance to sinefungin. If this is true then the question is, WHY are these cells growing slowly? Some hints may come from the reanalysis of the transcriptome and genome proposed above.The conclusion that there is a "master-switch" controlling differentiation is not supported buy the data and should deleted. Instead, I suspect that the changes seen in these cells may be related to a prolonged stress response, as suggested in a recent publication (10.1016/j.pt.2020.11.003). The cited publication also includes numerous references to stresses that can cause stumpy-like changes. Please read, consider, and cite. The question would then be why the cells retain this phenotype. Perhaps the resistant cells have mutated so as to make the stressed state permanent? could this explain the increased susceptibility to some other drugs? Is the phenotype lost really rapidly when selection is removed, or do the authors have to wait to select revertants? If the latter, the change must be genetic and the authors might be able to find it from the genotype results - especially if they also sequence revertants.Reviewer #2: Overall yes, but clarity in some areas is called for in 'Summary and General Comments'.Public health relevance is addressed nicely.Reviewer #3: The major problem with the conclusions is that all of the gene expression data is based on RNA levels and it is known that trypanosomes employ translational control as well so increased transcript numbers may not result automatically in increased protein levels. It would have been useful if the authors had demonstrated that some of the procyclic specific genes were actually expressed at the protein level (for example the procyclins/PARP/ EP/GPEET) as there are antibodies available and it would be easy to demonstrate surface expression of these proteins. Or if they had employed ribosomal profiling rather tha just RNA-seq to demonstrate that the upregulated PCF genes were being translated. In this context one experiment that should be done is to check the protein expression level of CPSF3 since they dismiss the idea of overexpression by saying there were no changes in RNA level but if the CPSF3 mRNA is more efficiently translated in a "PCF-like" context then they may be missing the actual resistance mechanism.With the metabolomics data they disucss several metabolites with changes in the resistant cell lines eg carnitine, orotate etc but they do not mention whther these metabolic changes link to any upregulated or downregulated genes in the RNA-seq data. This should be done and it should be made clear if there are any significant chnages in pyrimidine metabolic genes for example or genes related to L-carnitine metabolism or pathways L-carnitine is involved in.I cannot see anywhere where the authors have tested the stability of this resistance phenotype - is the phenotype lost in the absence of acoziborole, and if so how rapidly does it revert? In this light it would also have been interesting to see whether any live trypanosomes could have been recovered from an infected mouse (Lines 290-291).--------------------Editorial and Data Presentation Modifications?Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.Reviewer #1: Minor corrections (grammar or unclear):"There were small but significant decreases observed in three copies of the CBP1 gene". This should be changed to "There were small but significant decreases observed in mRNA encoding CBP1" followed by an reminder of what the function of CBP1 is, with an appropriate reference."HAT case number has" -> "HAT case numbers have" OR "The HAT case number has"for stage 1 and stage 2 treatment of HAT -> for treatment of stage 1 and stage 2 HATdownregulated, -> down-regulated; upregulated -> up-regulated."T. brucei brucei is infectious to livestock" -> T. brucei brucei and T. brucei rhodesiense are infectious..the disease can be fatal.. -> the disease is usually fatal.. (I think this is still true)procyclic (PCF) insect vector stages in the tsetse fly -> delete "insect vector""reduction in case number of the disease caused by T. b. gambiense" -> "reduction in T. b. gambiense case numbers"."Finally, abundance of PAD proteins" - should be "the abundances of transcripts encoding PAD proteins..." - plural needed, and proteins were not measured.Line 271: "|the cpsf3 gene" Gene should be in capital letters and italics."in clinical practise as.." -> "practice" ("Practise" is a verb.)Reviewer #2: My view is that operarational this is a major 'minor revision'.Reviewer #3: There are some minor changes required:Line 70: Only eflornithine is biologically species specific, it is policy that dictates the use of the other drugs, for example suramin is not used because of coinfection with filarial nematodes, not because T. gambiense is resistant to it. Also, the word disease should be inserted in front of stage-specific to distinguish it from parasite stages.Line 117: Lister 427 is a monomorphic strain with a defective differentiation pattern - authors should comment on this in the discussion, in particular as regards mitochondrial activation for example.Line 123 numbers should be given for doubling times.Line 267 "step chance" should be "step change"Line 284 insert the word partial before differentiation as there was no morphological differentiation.Lines 424-426 Fig 1. Legend to part B does not refer to the figure but talks about changes in EC50 whereas the figure is about doubling times.Line 426 The C is missing where the legend should refer to part C.--------------------Summary and General CommentsUse this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.Reviewer #1: See above for overall comments. The study is interesting but without more detailed analysis of the transcriptomes and genotype, including effects of removing the selection, the results are difficult to interpret. If the cells are resistant simply because they are growing more slowly, the reasons for the slow growth need to be examined.Reviewer #2: The authors describe the generation and characterization of an acoziborole-resistant bloodstream Trypanosoma brucei cell line. They report co-resistance to sinefungin and hypersensitivity to other drugs. Overall, it’s a straightforward manuscript, but one that I enjoyed reading and the work will be of value and interest to others in the community. However, as listed below, there are areas that need tidying before the work is suitable for publication.Line 123, cell doubling times lengthen (i.e. increase) not reduced (Fig 1B). In the legend to Fig 1B, the growth curve is not described – rather B) in the legend is referring to Fig 1C. And finally with respect to Fig 1B the cell densities per ml seem rather high (and don’t tally with what’s in the Materials and Methods for in vitro culture. Or am I looking at an in vivo growth curve? If in vitro are the resistant clones grown up in the presence of drug or not? None of the cultures, if these are batch cultures, appear to have reached stationary phase – this is particularly of note for the resistant cultures since at what density do they plateau out?More generally, 4 clones from the same resistant population are analysed, so the wider question is how representative is the resistance mechanism described in the current work? Of course, were a second resistant population analysed and it presented a different resistance phenotype, one would be content with reading the description of two different resistance phenotypes – so I have no problem with the single resistant population analysed butI see no indication that expression, at the protein level, of the expressed VSG is reduced, but much appears made of the changes in VSG expression seen at the level of transcriptomics. Is the 221 VSG actually translated at a lower level in the resistant population versus the parent? Unless the authors are clearer on the effect of resistance on VSG expression, the reader is left hanging – I’m not sure for instance that if say endo/exocytic rate were reduced this wouldn’t affect the amount of VSG on the actual cell surface.Did the authors complete any TEM – is the classic appearance of the VSG coat (e.g. as noted by Vickerman) evident all around the cell or is that surface coat now patchy or the cell surface changed in some other way evident in EM?Table 2 – would be helpful to know by reading (rather than dig through TriTrypDB) whether the several hypotheticals are T. brucei-specific trypanosomatid/kinetoplastid-specific, chromosome-internal or sub-telomeric. More details please.At the level of proteomics or immunoblotting is there any evidence for translation of procyclic marker proteins e.g. PPDK, PARP, transporters in the resistant cell line – the authors talk about a ‘differentiation event’ (or phenotype) (line 284) but I don’t see any evidence really for anything other than a bloodstream cell with an altered transcriptome and odd kintoplast-nucleus distance and the latter perhaps is a function of slow cell growth.How long did the authors growth the resistant mutants for – does the growth rate ever speed up? Is the resistance phenotype (or slow growth) retained after drug pressure is removed? These details were also missing but would be helpful to know.Reviewer #3: This study provides an interesting insight into novel mechanism of drug resistance in African trypanosomes and also provides new information about the differentiation process. It is interesting that the procyclin genses are upregulated as well as other PCF specific genes, since the procyclins are transcribed from specialise dloci by RNA polymerase I like the VSG genes so the transcriptional switch posited by the authors must affect the RNA Pol I stage regulated system as well as RNA Pol II transcribed genes. This resistance mechanism is unlikely to operate easily in the field as PCF-like forms are unlikely to survive in an immunocompetent mammalian host as the authors state.There are two major weaknesses, one is that the authors have not demonstrated that any of the upregulation at the RNA level leads to upregulation of the encoded proteins, trypanosomes display translational control so it is not automatic that increased mRNA leads to increased protein levels. The authors should mention this caveat in their discussion. The second is that they have identifed a phenomenon - "transcriptional differentiation" which accompanes the acquisition of acoziborole resistance but they have not identifed a mechanism whereby this leads to resistance.Overall the study is well-performed within the above limitations and is both novel and significant in increasing our understanding of the plasticity of trypanosome phenotypes.--------------------PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #1: Yes: Christine ClaytonReviewer #2: NoReviewer #3: NoFigure Files:While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.Data Requirements:Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.Reproducibility:To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols29 Sep 2021Submitted filename: acoziborole_resistance_manuscript_reviewers_comments_FINAL.pdfClick here for additional data file.13 Oct 2021Dear Prof. Barrett,Thank you very much for submitting your manuscript "Transcriptional differentiation of Trypanosoma brucei during in vitro acquisition of resistance to acoziborole" for consideration at PLOS Neglected Tropical Diseases.Your manuscript has been re-reviewed by the original three reviewers. I'm happy to tell you that they feel you have addressed their concerns and that they all recommend publication. Reviewer 1 has a few minor edits that they would like to see incorporated so I am sending the manuscript back to you so you can consider those recommendations. I shall be happy to accept your manuscript once you have had an opportunity to address those recommendations.Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.When you are ready to resubmit, please upload the following:[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript.Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).Important additional instructions are given below your reviewer comments.Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.Sincerely,Margaret A Phillips, Ph.D.Deputy EditorPLOS Neglected Tropical DiseasesMargaret PhillipsDeputy EditorPLOS Neglected Tropical Diseases***********************Your manuscript has been re-reviewed by the original three reviewers. I'm happy to tell you that they feel you have addressed their concerns and that they all recommend publication. Reviewer 1 has a few minor edits that they would like to see incorporated so I am sending the manuscript back to you so you can consider those recommendations. I shall be happy to accept your manuscript once you have had an opportunity to address those recommendations.Reviewer's Responses to QuestionsKey Review Criteria Required for Acceptance?As you describe the new analyses required for acceptance, please consider the following:Methods-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?-Is the study design appropriate to address the stated objectives?-Is the population clearly described and appropriate for the hypothesis being tested?-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?-Were correct statistical analysis used to support conclusions?-Are there concerns about ethical or regulatory requirements being met?Reviewer #1: yesReviewer #2: Yes, to all criteria requested.Reviewer #3: The revised version is accepatble--------------------Results-Does the analysis presented match the analysis plan?-Are the results clearly and completely presented?-Are the figures (Tables, Images) of sufficient quality for clarity?Reviewer #1: all OKReviewer #2: Yes, to all criteria requested.Reviewer #3: The revised version is acceptable--------------------Conclusions-Are the conclusions supported by the data presented?-Are the limitations of analysis clearly described?-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?-Is public health relevance addressed?Reviewer #1: Yes now all OKReviewer #2: Yes, to all criteria requested.Reviewer #3: The manuscript is improved by the authors responses to the reviewers and is acceptable for publication in my opinion.--------------------Editorial and Data Presentation Modifications?Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.Reviewer #1: noReviewer #2: (No Response)Reviewer #3: Accept--------------------Summary and General CommentsUse this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.Reviewer #1: This paper is very much improved. There are only a few minor things now, which have resulted from new introductions to the text.I noted that the authors talk about procyclic and stumpy in the Introduction but don’t actually say what stumpy forms are, which would be a problem for potential readers who don’t work on trypanosomes but are interested in the benzoxoboroles. A couple of sentences that say what stumpy forms are and list genes important for (and markers for) stumpy differentiation are needed. Aslo somewhere the authors need to describe the morphological differences between the three forms considered.ine 116 _ change to “a partial switch towards procyclic mRNA abundances”. I find the word “phenotype “ a bit too strong. Many readers might assume that “phenotype” means morphology, which was not much changed.Line 1272 - “transcript” not “transcription”.“Transcripts associated with proteins involved in stage-specific regulation of mRNA (e.g. reduction in PARN-1; Tb927.8.2850) were also significantly altered. “ The evidence that PARN1 is involved in stage-specific regulation of mRNA is based on artificial over-expression. The effects on differentiation have not been measured because the only paper (Utter et al, not cited) is with non-differentiation-competent cells. A procyclic knock-out grew almost normally and RNAi had no effect in bloodstream forms. Actually, looking at the resutls of the microarrays, they are really wierd -a whole cluster from one particular region of chromosome 9 is all up about 2-fold. It’s inducible so unlikely to be a gene duplication. The only genes affected that are linked to differentiation are the BARP genes, which are actually a marker for some salivary gland epimastigotes. in that context, there’s an increase in HAP2 mRNA in the acoziborole resistant cells, which suggests to me a stress response since it’s a gamete protein. No harm in mentioning PARN1 but I’d be careful about saying what it does. If you want to find proteins implicated in control of gene expression in the bloodstream-stumpy-procyclic transition you would be on more solid ground with the known markers and signalling proteins, and with ZC3H11 and ZC3H22 (Tb927.7.2680).I was intrigued by the set of proteins that are affected in the slender-vs-stumpy or slender -vs-procyclic comparisons, but not in the acoziborole-resistant cells. For stumpy forms they seem to be dominated by cytoskeletal proteins and histones - the stumpy cells aren’t dividing and the resistant cells are.Reviewer #2: (No Response)Reviewer #3: The manuscript is improved by the authors responses to the reviewers and is acceptable for publication in my opinion.--------------------PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #1: Yes: Christine ClaytonReviewer #2: NoReviewer #3: NoFigure Files:While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.Data Requirements:Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.Reproducibility:To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocolsReferencesPlease review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article's retracted status in the References list and also include a citation and full reference for the retraction notice.21 Oct 2021Submitted filename: acoR_manuscript_reviewers_comments_round2.pdfClick here for additional data file.21 Oct 2021Dear Prof. Barrett,We are pleased to inform you that your manuscript 'Transcriptional differentiation of Trypanosoma brucei during in vitro acquisition of resistance to acoziborole' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.IMPORTANT: The editorial review process is now complete. 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All press must be co-ordinated with PLOS.Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.Best regards,Margaret A Phillips, Ph.D.Deputy EditorPLOS Neglected Tropical DiseasesMargaret PhillipsDeputy EditorPLOS Neglected Tropical Diseases***********************************************************5 Nov 2021Dear Prof. Barrett,We are delighted to inform you that your manuscript, "Transcriptional differentiation of Trypanosoma brucei during in vitro acquisition of resistance to acoziborole," has been formally accepted for publication in PLOS Neglected Tropical Diseases.We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. 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