Literature DB >> 35993778

Transcriptomic Data Sets for Zymomonas mobilis 2032 during Fermentation of Ammonia Fiber Expansion (AFEX)-Pretreated Corn Stover and Switchgrass Hydrolysates.

Yaoping Zhang1, Kevin S Myers1, Michael Place1, Jose Serate1, Dan Xie1, Edward Pohlmann1, Alex La Reau1, Robert Landick1, Trey K Sato1.   

Abstract

The transcriptomes of Zymomonas mobilis 2032 were captured during the fermentation of ammonia fiber expansion (AFEX)-pretreated corn stover and switchgrass hydrolysates containing different concentrations of glucose and xylose. RNA samples were collected when Z. mobilis was fermenting glucose or xylose. Here, we present transcriptome sequencing (RNA-Seq) data obtained during separate phases of glucose or xylose consumption.

Entities:  

Year:  2022        PMID: 35993778      PMCID: PMC9476961          DOI: 10.1128/mra.00564-22

Source DB:  PubMed          Journal:  Microbiol Resour Announc        ISSN: 2576-098X


ANNOUNCEMENT

Zymomonas mobilis is a natural ethanologen with a number of traits shared by other well-known industrial biofuel producers. Z. mobilis 2032 is a derivative of the model strain ZM4 with multiple directed and evolutionary engineering modifications that enable diauxic catabolism of xylose (1). Previous results indicated that the 2032 strain can ferment glucose to ethanol in both 6% and 9% glucan loading ammonia fiber expansion (AFEX)-pretreated corn stover hydrolysate (ACSH) and 7% glucan loading AFEX-pretreated switchgrass hydrolysate (ASGH) (1, 2). Compared to fermentation of 6% ACSH or 7% ASGH, Z. mobilis 2032 grew more slowly in 9% ACSH, consuming little xylose after glucose depletion (3). This inhibition of xylose utilization is probably caused by osmotic stress responses and/or higher concentrations of inhibitors in 9% ACSH. To better understand the physiological responses of Z. mobilis during diauxic fermentation of glucose and xylose in the different hydrolysates, we collected Z. mobilis 2032 samples at time points at which glucose or xylose was being primarily consumed and sequenced the RNA for transcriptome analyses. Fermentation of Z. mobilis 2032 was conducted in 6% and 9% ACSH and in 7% ASGH in bioreactors as described previously (1). Glucose and xylose concentrations were monitored with a YSI 2700 Biochemistry Analyzer (YSI, Inc., Yellow Springs, OH) during the fermentation. For transcriptome analyses, cells were collected at time points at which glucose or xylose was being primarily consumed, and RNA was isolated and treated with DNase as described previously (4), with at least three biological replicates (Table 1). RNA samples were delivered to the Joint Genome Institute (JGI) (Berkeley, CA) for library preparation and sequencing. After rRNA removal via the Ribo-Zero rRNA removal kit (Illumina, San Diego, CA) and paired-end library generation using the Illumina TruSeq stranded mRNA preparation kit, the libraries were sequenced with 100-bp paired-end reads on an Illumina HiSeq 2000 system. Reads were trimmed using Trimmomatic (version 0.39) (5) and were mapped to the Z. mobilis 2032 genome (GenBank accession number CP023677) using bwa-mem (version 0.7.17-h5bf99c6_8) (6) with default parameters. Alignment files were cleaned and sorted with Picard tools (version 2.26.10) (https://broadinstitute.github.io/picard) and SAMtools (version 1.2) (7). Aligned reads were mapped to gene boundaries using HTSeq (version 0.6.0) (8) and normalized using reads per kilobase per million mapped reads (RPKM). Significant differential expression (DE) was determined to be at least a 2-fold change in gene expression with an edgeR pairwise-analysis false-discovery rate (FDR) of ≤0.05 (9). There were no genes with significant DE when 7% ASGH and 6% ACSH were compared during the glucose consumption phases and only 2 genes with significant DE during the xylose consumption phases (Fig. 1). A total of 610 and 530 genes with significant DE were identified in comparisons of 9% and 6% ACSH during the glucose and xylose consumption phases, respectively (Fig. 1). The small overlap of the genes with significant DE in the different phases suggests unique responses to each hydrolysate condition.
TABLE 1

Summary of RNA-Seq sample data

SampleGrowth mediumSugar consumption phaseReplicate no.BioSample accession no.
Glu_6_A6% ACSHGlucose1 GSM6053149
Glu_6_B6% ACSHGlucose2 GSM6053150
Glu_6_C6% ACSHGlucose3 GSM6053151
Glu_6_D6% ACSHGlucose4 GSM6053152
Glu_6_E6% ACSHGlucose5 GSM6053153
Xyl_6_A6% ACSHXylose1 GSM6053154
Xyl_6_B6% ACSHXylose2 GSM6053155
Xyl_6_C6% ACSHXylose3 GSM6053156
Xyl_6_D6% ACSHXylose4 GSM6053157
Glu_7_A7% ASGHGlucose1 GSM6053158
Glu_7_B7% ASGHGlucose2 GSM6053159
Glu_7_C7% ASGHGlucose3 GSM6053160
Xyl_7_A7% ASGHXylose1 GSM6053161
Xyl_7_B7% ASGHXylose2 GSM6053162
Xyl_7_C7% ASGHXylose3 GSM6053163
Glu_9_A9% ACSHGlucose1 GSM6053164
Glu_9_B9% ACSHGlucose2 GSM6053165
Glu_9_C9% ACSHGlucose3 GSM6053166
Glu_9_D9% ACSHGlucose4 GSM6053167
Glu_9_E9% ACSHGlucose5 GSM6053168
Xyl_9_A9% ACSHXylose1 GSM6053169
Xyl_9_B9% ACSHXylose2 GSM6053170
Xyl_9_C9% ACSHXylose3 GSM6053171
Xyl_9_D9% ACSHXylose4 GSM6053172
Xyl_9_E9% ACSHXylose5 GSM6053173
FIG 1

Summary of genes with significant DE by RNA-Seq under different growth conditions. (A) All genes with significant DE. (B) Genes with a significant decrease in expression, relative to the corresponding 6% ACSH growth condition. (C) Genes with a significant increase in expression, relative to the corresponding 6% ACSH growth condition. Xyl indicates the xylose consumption phase, while Glu indicates the glucose consumption phase. Note that 7% ASGH glucose versus 6% ACSH glucose had no genes with significant DE, and there were no genes with significant DE with an increase in expression when 7% ASGH xylose was compared to 6% ACSH xylose. Venn diagram circles are not proportional, to show the lack of overlap.

Summary of genes with significant DE by RNA-Seq under different growth conditions. (A) All genes with significant DE. (B) Genes with a significant decrease in expression, relative to the corresponding 6% ACSH growth condition. (C) Genes with a significant increase in expression, relative to the corresponding 6% ACSH growth condition. Xyl indicates the xylose consumption phase, while Glu indicates the glucose consumption phase. Note that 7% ASGH glucose versus 6% ACSH glucose had no genes with significant DE, and there were no genes with significant DE with an increase in expression when 7% ASGH xylose was compared to 6% ACSH xylose. Venn diagram circles are not proportional, to show the lack of overlap. Summary of RNA-Seq sample data These transcriptomic data sets will enable investigators to identify the physiological responses to lignocellulose conversion that impact the production of sustainable biofuels by Z. mobilis.

Data availability.

Raw RNA-Seq reads are available at NCBI GEO under accession number GSE201229.
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Journal:  Nat Biotechnol       Date:  2009-10       Impact factor: 54.908

2.  Using DNA microarrays to assay part function.

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Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

4.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

5.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

6.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
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7.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

8.  Controlling microbial contamination during hydrolysis of AFEX-pretreated corn stover and switchgrass: effects on hydrolysate composition, microbial response and fermentation.

Authors:  Jose Serate; Dan Xie; Edward Pohlmann; Charles Donald; Mahboubeh Shabani; Li Hinchman; Alan Higbee; Mick Mcgee; Alex La Reau; Grace E Klinger; Sheena Li; Chad L Myers; Charles Boone; Donna M Bates; Dave Cavalier; Dustin Eilert; Lawrence G Oates; Gregg Sanford; Trey K Sato; Bruce Dale; Robert Landick; Jeff Piotrowski; Rebecca Garlock Ong; Yaoping Zhang
Journal:  Biotechnol Biofuels       Date:  2015-11-14       Impact factor: 6.040

9.  Complete genome sequence and the expression pattern of plasmids of the model ethanologen Zymomonas mobilis ZM4 and its xylose-utilizing derivatives 8b and 2032.

Authors:  Shihui Yang; Jessica M Vera; Yaoping Zhang; Jeff Grass; Giannis Savvakis; Oleg V Moskvin; Yongfu Yang; Sean J McIlwain; Yucai Lyu; Irene Zinonos; Alexander S Hebert; Joshua J Coon; Donna M Bates; Trey K Sato; Steven D Brown; Michael E Himmel; Min Zhang; Robert Landick; Katherine M Pappas
Journal:  Biotechnol Biofuels       Date:  2018-05-02       Impact factor: 6.040

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