Extensive age-dependent loss of antibody diversity in naturally short-lived turquoise killifish.

Aging individuals exhibit a pervasive decline in adaptive immune function, with important implications for health and lifespan. Previous studies have found a pervasive loss of immune-repertoire diversity in human peripheral blood during aging; however, little is known about repertoire aging in other immune compartments, or in species other than humans. Here, we perform the first study of immune-repertoire aging in an emerging model of vertebrate aging, the African turquoise killifish (Nothobranchius furzeri). Despite their extremely short lifespans, these killifish exhibit complex and individualized heavy-chain repertoires, with a generative process capable of producing millions of distinct productive sequences. Whole-body killifish repertoires decline rapidly in within-individual diversity with age, while between-individual variability increases. Large, expanded B-cell clones exhibit far greater diversity loss with age than small clones, suggesting important differences in how age affects different B-cell populations. The immune repertoires of isolated intestinal samples exhibit especially dramatic age-related diversity loss, related to an elevated prevalence of expanded clones. Lower intestinal repertoire diversity was also associated with transcriptomic signatures of reduced B-cell activity, supporting a functional role for diversity changes in killifish immunosenescence. Our results highlight important differences in systemic vs. organ-specific aging dynamics in the adaptive immune system.

Introduction

The adaptive immune system undergoes a severe and systemic decline in proper function with age, resulting in higher susceptibility to a wide range of infections and decreased efficacy of vaccination in elderly individuals (Ademokun et al., 2010; Kogut et al., 2012; Dunn-Walters and Ademokun, 2010). In the humoral immune system, aging is accompanied by a decline in naïve B-cell output from the primary lymphoid organs; impaired production of specific antibodies in response to antigenic challenge; and a decline in antibody quality (Ademokun et al., 2010; Kogut et al., 2012; Sasaki et al., 2011; Aberle et al., 2013), as well as impairments in the establishment of novel immune memory (Aberle et al., 2013). These changes are major contributors to a generalized immunosenescent phenotype that significantly impairs health and quality of life in the elderly.

The efficacy of the humoral immune system rests on its ability to generate an enormous array of different antibody sequences, with a correspondingly vast range of antigen specificities, and to progressively adjust the composition of this antibody population in response to antigen exposure (Schatz and Swanson, 2011; Di Noia and Neuberger, 2007; Magor, 2015; Elhanati et al., 2015). Sampling the resulting repertoire of antibody sequences in an individual using high-throughput sequencing can yield important insights into the diversity, clonal composition, and history of antibody-mediated immunity in that organism, as well as the effect of age, antigen exposure, and other factors on the diversity and functionality of the adaptive immune system (Weinstein et al., 2009; de Bourcy et al., 2017; Miho et al., 2018).

In humans, antibody-repertoire sequencing has uncovered a number of important age-related changes, including reduced numbers of clones and unique sequences, increased baseline mutation, more frequent and larger clonal expansions, impaired B-cell selection, and a shift toward the memory compartment (de Bourcy et al., 2017; Jiang et al., 2013; Wang et al., 2014). The responsiveness of the peripheral repertoire to vaccination is also impaired during aging (de Bourcy et al., 2017; Wang et al., 2014). While within-individual repertoire diversity declines with age, between-individual variability increases, with repertoires from older individuals differing more from one another than those from young individuals (de Bourcy et al., 2017).

Previous work in humans, however, has been limited by small sample sizes, a lack of temporal resolution, or a restriction to peripheral blood samples, which are known to systematically underrepresent the majority of B-cells resident in other organs and tissues (Siegrist and Aspinall, 2009; Tabibian-Keissar et al., 2016). Very little is known about how repertoire aging differs between distinct organs; in particular, almost nothing is known about how aging affects antibody repertoires at mucosal surfaces, which represent a crucial interface between the body and its microbial environment (Belkaid and Hand, 2014; Magadan et al., 2019). Even less is known about how aging might affect the antibody repertoires of vertebrates other than mice and humans.

In this study, we introduce the naturally short-lived turquoise killifish (Nothobranchius furzeri) (Bradshaw and Valenzano, 2020; Hu and Brunet, 2018; Poeschla and Valenzano, 2020; Reichwald et al., 2015) as a model for adaptive immunosenescence. Here, we perform the first immune-repertoire sequencing experiments in this species, demonstrating that adult killifish express diverse and individualized heavy-chain repertoires that undergo rapid loss of diversity with age. The age-dependent loss of the antibody-repertoire diversity primarily affects the composition of expanded clones, with small naïve clones exhibiting much smaller age-related changes. By sequencing the repertoires of isolated intestinal samples, we further find that the killifish intestinal antibody repertoire exhibits much more dramatic age-dependent diversity loss than the body as a whole, possibly due to a much higher prevalence of expanded clones in the intestine, and that this loss of diversity is associated with gene expression changes indicating reduced B-cell activity. Taken together, our results reveal substantial differences between whole-body and organ-specific immune-repertoire aging, and establish the turquoise killifish as a powerful model for studying adaptive immune senescence.

Results

Establishing immunoglobulin sequencing in the turquoise killifish

To investigate the effect of age on the B-cell receptor repertoire diversity and composition in turquoise killifish, we implemented an RNA-based repertoire-sequencing protocol based on the published protocol of Turchaninova et al., 2016, using template switching (Zajac et al., 2013) to add unique molecular identifiers (UMIs) to each RNA transcript of the immunoglobulin heavy chain (Figure 1; Bradshaw and Valenzano, 2020) to correct for errors and biases in abundance arising during PCR and Illumina sequencing (Vollmers et al., 2013). To test the validity and replicability of results obtained using this protocol, we performed three replicate library preps on whole-body total RNA samples from four adult (8-week-old) adult male turquoise killifish from the short-lived GRZ strain (Figure 1—figure supplement 1). Independent repertoires from the same individual showed a high degree of similarity in their clonal composition, with an average inter-replicate correlation in clone size of r = 0.89 (Figure 1—figure supplement 2). Inter-repertoire divergences computed with the published repertoire dissimilarity index (RDI) metric (Bolen et al., 2017) consistently identified replicates from the same individual as much more similar than repertoires from different individuals (Figure 1—figure supplement 3), demonstrating that this protocol is capable of accurately and reproducibly reconstructing the expressed heavy-chain repertoires of individual killifish.

Figure 1.

Immunoglobulin sequencing from turquoise-killifish total RNA samples.

Each sample undergoes reverse transcription with template switching to attach a 5' adaptor sequence and unique molecular identifier (UMI), followed by multiple rounds of PCR amplification and addition of Illumina sequencing adaptors. Libraries are then pooled, undergo size selection, and are sequenced on an Illumina MiSeq sequencing machine.

Four individuals from the 8-week-old group in Supplementary file 2c were each independently sequenced three times: once from a separate whole-body total RNA sample (replicate 1) and twice independently from a second sample (replicates 1 and 2).

(A) Boxplots of inter-replicate correlation in clone sizes across the four individuals in the pilot experiment (Figure 1—figure supplement 1). (B) Example scatter plot for each individual, showing the relationship between the size of a clone in replicate 1 and the same clone in replicate 2.

(A) UPGMA clustering dendrogram on repertoire pilot replicates (Figure 1—figure supplement 1), based on pairwise repertoire dissimilarity index (RDI) distances computed on the V/J composition of each replicate and colored according to individual origin. (B) Principal coordinate analysis (PCoA) of pairwise VJ-RDI distances between all replicates, colored by individual origin.

Figure 1—figure supplement 1.

Experimental design of the IgSeq pilot experiment in the turquoise killifish.

Four individuals from the 8-week-old group in Supplementary file 2c were each independently sequenced three times: once from a separate whole-body total RNA sample (replicate 1) and twice independently from a second sample (replicates 1 and 2).

Figure 1—figure supplement 2.

Replicability of IgSeq results on total-body RNA.

(A) Boxplots of inter-replicate correlation in clone sizes across the four individuals in the pilot experiment (Figure 1—figure supplement 1). (B) Example scatter plot for each individual, showing the relationship between the size of a clone in replicate 1 and the same clone in replicate 2.

Figure 1—figure supplement 3.

Clustering of replicates in control libraries.

(A) UPGMA clustering dendrogram on repertoire pilot replicates (Figure 1—figure supplement 1), based on pairwise repertoire dissimilarity index (RDI) distances computed on the V/J composition of each replicate and colored according to individual origin. (B) Principal coordinate analysis (PCoA) of pairwise VJ-RDI distances between all replicates, colored by individual origin.

Aging in whole-body killifish repertoires

To investigate the effect of age on the structure and diversity of killifish antibody repertoires, we performed whole-body immunoglobulin sequencing on 32 adult male turquoise killifish from the short-lived GRZ strain (Hu and Brunet, 2018) at four different ages from early adulthood to late life (Figure 2A and Supplementary file 2a-d). The repertoire of each individual comprised some number of unique heavy-chain sequences, each of which could be classified by clonal identity (the ‘clonal repertoire’) and V/J usage (the ‘VJ repertoire’).

Figure 2.

Aging in whole-body killifish IGH repertoires.

(A) Experimental design. Adult male GRZ-strain turquoise killifish were sacrificed at 39, 56, 73, and 128 days post-hatching, flash-frozen and homogenized. (B–E) Alpha-diversity spectra, indicating average within-individual repertoire diversity for each age group and diversity order (*: 0.05 ≤ 0.01, **: 0.01≤ p ≤ 0.001, Kruskal-Wallis permutation test, Appendix 1—note 7). (B) Clonal alpha-diversity spectra. (C) VJ alpha-diversity spectra, all clones. (D) VJ alpha-diversity spectra, large clones (>4 unique sequences) only. (E) VJ alpha-diversity spectra, small clones (<5 unique sequences) only. (F) VJ alpha-diversity ratios for old vs. young killifish at each diversity order, for small (dashed lines) or large (solid lines) clones. Color indicates the older age group being compared to young (39 days) fish. (G) Normalized VJ beta-diversity spectra, indicating between-individual variability in repertoire composition for each age group and diversity order. (H) Distributions of pairwise repertoire dissimilarity index (RDI) distances between individuals in each age group (***: p ≤ 0.001, Mann-Whitney U tests for pairwise age differences), based on the VJ composition of each individual’s repertoire. (I) Principal coordinate analysis (PCoA) of pairwise RDI distances for each age group, visualizing the progressively greater dispersion seen at later ages. Each curve in (B–G) represents the mean across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

(A) A clone is a group of B-cells descended from the same naïve ancestor cell. In this figure, a group of 28 unique sequences in an antibody repertoire, each representing a single cell, is partitioned into five groups based on their inferred clonal identity. (B) Each developing B-cell selects a single V, D, and J gene segment from those present in the native immunoglobulin heavy-chain (IGH) locus and recombines them together to produce its antigen-binding sequence. In this figure, the same 28 sequences are instead grouped by the V and J segments their naïve ancestors selected during development. As each developing B-cell selects from the same range of possible gene segments, this results in multiple clones being grouped together in a single V/J category, resulting in only three groups.

Clonal (top row) or VJ (other rows) diversity spectra of individual turquoise killifish of different ages. Each curve represents the mean Hill diversity for that individual across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

Color indicates type of diversity (clonal vs. VJ, etc.) being tested; see main text and Appendix 1—note 7 for more details.

(A) Cumulative clone-size distributions for each individual in the aging dataset. (B) V/J combinations present in each individual whole-body repertoire in the dataset, with each point representing a single V/J combination in a single individual, its x-coordinate indicating the number of unique IGH sequences assigned to that V/J combination in that individual, and its y-coordinate indicating the average clone size among those sequences.

The diversity of a population is a measure of the number (a.k.a. the richness) and relative frequency of different subdivisions within that population. For B-cell repertoires, diversity can be calculated over the different clonal lineages detected in a sample, or over different variable-region gene segment combinations.

To quantify immune-repertoire diversity in killifish heavy-chain repertoires, we computed Hill diversity spectra (Appendix 1—note 1), which provide a holistic overview of the diversity structure of a population (in this case, a repertoire) (Miho et al., 2018; Hill, 1973; Jost, 2006; Jost, 2007). Briefly, each Hill spectrum reports the ‘effective richness’ of a repertoire across a range of diversity orders; higher effective richness corresponds to a more diverse repertoire. At low diversity orders, species of different sizes are weighted more equally in the diversity calculation, while at higher orders, less-abundant species are progressively downweighted relative to more-abundant groups (Appendix 1—note 1). For the clonal repertoire, each clonotype (set of unique sequences descended from a single naïve ancestor B-cell) was designated a separate species; for the VJ repertoire, clonotypes with the same V/J identity were grouped together.

Separate spectra were computed for the clonal and VJ repertoires of each individual, and these individual spectra were used to compute averaged alpha-diversity spectra for each age group and repertoire type. For each diversity order, we tested for a significant age effect on repertoire diversity using a permutation test on the Kruskal-Wallis H statistic (Materials and methods).

The clonal diversity (Figure 2—figure supplement 1) of the whole-body killifish repertoire exhibited a significant decline with age (p < 0.05) at high diversity orders (Figure 2B, Figure 2—figure supplements 2–3), indicating a significant and extremely rapid age-related decline in the diversity of the largest B-cell clones. In contrast, lower-order clonal diversity exhibited no significant change with age, suggesting that the overall composition of the whole-body repertoire remains relatively unchanged. Since the B-cell clonal repertoire is overwhelmingly dominated by small, predominantly naïve clones (Figure 2—figure supplement 4A), low-order clonal diversity measurements are primarily driven by changes in the diversity of small clones. As such, these results indicate that the composition of small clones in the killifish antibody repertoire is much less sensitive to the effects of aging than that of large, expanded clones.

Figure 2—figure supplement 1.

Clonal and V/J diversity in antibody repertoires.

(A) A clone is a group of B-cells descended from the same naïve ancestor cell. In this figure, a group of 28 unique sequences in an antibody repertoire, each representing a single cell, is partitioned into five groups based on their inferred clonal identity. (B) Each developing B-cell selects a single V, D, and J gene segment from those present in the native immunoglobulin heavy-chain (IGH) locus and recombines them together to produce its antigen-binding sequence. In this figure, the same 28 sequences are instead grouped by the V and J segments their naïve ancestors selected during development. As each developing B-cell selects from the same range of possible gene segments, this results in multiple clones being grouped together in a single V/J category, resulting in only three groups.

Figure 2—figure supplement 2.

Individual diversity spectra in killifish whole-body repertoires.

Clonal (top row) or VJ (other rows) diversity spectra of individual turquoise killifish of different ages. Each curve represents the mean Hill diversity for that individual across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

Figure 2—figure supplement 3.

p-Values of Kruskal-Wallis permutation tests for an age effect (Appendix 1—note 7) in whole-body killifish IGH repertoires at different Hill diversity orders.

Color indicates type of diversity (clonal vs. VJ, etc.) being tested; see main text and Appendix 1—note 7 for more details.

Figure 2—figure supplement 4.

Clone size distributions in killifish whole-body repertoires.

(A) Cumulative clone-size distributions for each individual in the aging dataset. (B) V/J combinations present in each individual whole-body repertoire in the dataset, with each point representing a single V/J combination in a single individual, its x-coordinate indicating the number of unique IGH sequences assigned to that V/J combination in that individual, and its y-coordinate indicating the average clone size among those sequences.

In contrast with the rapid age-related declines observed in high-order clonal diversity, the VJ diversity of the killifish repertoire exhibited no significant age-related change at any diversity order (Figure 2C). Examining the clone-size distribution of each V/J combination (Figure 2—figure supplement 4B) revealed that even the largest V/J combinations in each age group are overwhelmingly dominated by small clones, suggesting that the observed lack of an age effect on VJ diversity was due to the observed age-insensitivity of small clones (Figure 2B). To test this hypothesis, we filtered the repertoire dataset to separate sequences from small and large clones and computed VJ diversity repertoires for each subset (Figure 2D–E). While both small and large clones in isolation showed a significant age effect on VJ diversity, the relative reduction in VJ alpha diversity with age was dramatically stronger for large clones, an effect observed across all diversity orders (Figure 2F). As suggested by the clonal-diversity results, therefore, the repertoire diversity of large (expanded) clones in the killifish whole-body repertoire appears to be far more age-sensitive than that of small (predominantly naïve) clones.

In addition to the average within-individual diversity of a population (alpha diversity), the between-individual variation in composition (beta diversity) can provide important insights into repertoire development and evolution. Previous studies of human peripheral blood repertoires have suggested a decrease in alpha diversity but an increase in beta diversity with age (Gibson et al., 2009; de Bourcy et al., 2017). In our dataset, VJ beta-diversity spectra (Appendix 1) indicated a large age-related increase in beta diversity across a wide range of diversity orders (Figure 2G), indicating a similar pattern of progressive individualization in repertoire composition with age. Concordantly, older killifish also exhibited significantly greater pairwise RDI distances (Bolen et al., 2017), indicating progressive divergence in repertoire composition (Figure 2H–I). As in humans, therefore, younger killifish exhibit antibody repertoires that are significantly more similar to one another, which then become increasingly distinct and individualized as the cohort increases in age.

The killifish generative repertoire

The naïve sequence diversity of the antibody heavy-chain repertoire depends on the molecular processes underlying the generation of novel sequences in developing B-cells: random selection of V, D, and J segments during VDJ recombination; deletions and palindromic (P-) insertions at the ends of conjoined segments; and nonpalindromic (N-) insertions between segments (Schatz and Swanson, 2011; Schroeder and Cavacini, 2010). Each of these contributes diversity to the overall generative process, increasing the variety of sequences that can be generated. Excluding nonfunctional sequences, the human generative process has an estimated Shannon entropy of roughly 70 bits, corresponding to a first-order Hill diversity of roughly 1021 possible unique sequences (Elhanati et al., 2015). However, little is known about how this generative diversity varies across species, or how it changes during aging.

To gain insight into these generative processes in the turquoise killifish, we used IGoR (Marcou et al., 2018) to infer models of sequence generation from killifish repertoire data. In training these models, we restricted the dataset to nonfunctional naïve sequences, in order to avoid distortions introduced by positive and negative selection in the primary lymphoid organs (Elhanati et al., 2015; Marcou et al., 2018). As is often the case with RNA data, the number of naïve nonfunctional sequences available per individual was frequently low; hence, to better capture low-probability events in the generative process, we inferred models from pooled data from multiple individuals in the same age group. As the parameters of the generative model are typically very similar across conspecific individuals (Figure 3—figure supplements 1–2), especially in an inbred line, pooling data like this is a useful way to infer more robust generative models using IGoR (Marcou 2019, personal communication).

Figure 3—figure supplement 1.

Individual IGoR-inferred insertion/deletion distributions (Figure 3A) for individuals in the pilot dataset (Figure 1—figure supplement 1).

Figure 3—figure supplement 2.

Individual IGoR-inferred segment-usage distributions (Figure 3B) for individuals in the pilot dataset (Figure 1—figure supplement 1).

To model the generative process in its baseline state, we first inferred a model of the killifish generative repertoire from the four 8-week-old adult male individuals used in the pilot study (Figure 1—figure supplement 1). Using this model, we estimated a total raw entropy for the killifish generative repertoire of roughly 33 bits (Figure 3A). Of these 33 bits, roughly 8 arise from variability in VDJ segment choice, 12 from variability in the number and composition of junctional N-insertions, and 11 from P-insertions and deletions. Accounting for convergent production of identical sequences via different recombination events, and for events that give rise to nonfunctional nucleotide sequences (e.g. due to frame shift) reduced this initial raw estimate by 10 bits.

Figure 3.

The killifish generative repertoire.

(A) Entropy composition of the generative process from four 8-week-old GRZ-strain adult male turquoise killifish. (B) Probability distributions of junctional N-insertions in the same dataset. (C) P-insertions and deletion distributions inferred from the same dataset, with P-insertions modeled as negative deletions. (D) Boxplots of total recombination entropy values for models inferred separately for each individual in the 32-individual aging cohort (p = 0.43, Kruskal-Wallis one-way analysis of variance [ANOVA] for an age effect).

The stated p-values are from Kruskal-Wallis one-way analysis-of-variance tests for an age effect.

Before initial selection in the primary lymphoid organs, therefore, the killifish generative process has an estimated Shannon entropy of roughly 23 bits (Figure 3A), corresponding to a first-order Hill diversity of roughly 107 possible unique sequences. While, as in humans, only a small fraction of potential diversity will actually be generated in any single individual, this nevertheless represents a highly complex and sophisticated system capable of generating highly individualized IGH repertoires.

While impressive, the potential generative diversity of the killifish repertoire is nevertheless vastly lower than in humans, with a difference in productive generative entropy of almost 50 bits (Elhanati et al., 2015). While all components of the generative process exhibit lower entropies in killifish than in humans, by far the greatest difference lies in the junctional N-insertions, which contribute almost 40 bits more to the generative entropy of the human repertoire than that of killifish. The difference in the productive generative entropy between killifish and human arises from the distributions of N-insertions inferred from killifish and human data: in humans, these distributions peak at around 5 nt per junction and often yield insertions of 10–20 nt (Elhanati et al., 2015), while in killifish the insertion distribution peaks at 0 nt per junction, and sequences with more than 5 nt of insertions at either junction are very rare (Figure 3B and Figure 3—figure supplement 1). Since N-insertions are the dominant source of sequence diversity in human repertoires, the large reduction in N-insertions in killifish relative to humans unsurprisingly results in a much lower overall generative diversity for the killifish adaptive immune system.

The relative lack of change in the small-clone antibody repertoire in older turquoise killifish (Figure 2B–F) suggested to us that the diversity of the generative process in the primary lymphoid organs might remain relatively intact throughout the killifish lifespan. To test this hypothesis, we trained separate IGoR models for each individual in the 32-fish aging cohort (Figure 2A, Figure 3—figure supplements 3–4) and tested for an effect of age on the generative diversity inferred for each individual. As expected, no age effect was found in either total generative diversity (Figure 3D) or the contributions of different diversification processes (Figure 3—figure supplement 5). It therefore appears that, while some aspects of the killifish antibody repertoire certainly decline with age, the entropy of the generative process is not among them.

Figure 3—figure supplement 3.

Individual IGoR-inferred insertion/deletion distributions (Figure 3A) for all individuals in the whole-body killifish dataset (Figure 2A and Supplementary file 2c).

Figure 3—figure supplement 4.

Individual IGoR-inferred segment-usage distributions (Figure 3B) for all individuals in the whole-body killifish dataset (Figure 2A and Supplementary file 2c).

Figure 3—figure supplement 5.

Boxplots of the entropy contributions of (A) gene choice, (B) N-insertions, and (C) P-insertions and deletions to the generative repertoires of individual turquoise killifish at different ages (Figure 2A and Supplementary file 2c).

The stated p-values are from Kruskal-Wallis one-way analysis-of-variance tests for an age effect.

Effect of age and microbiota transfer on killifish intestinal repertoires

The populations of B-lymphocytes associated with mucosal epithelia play a crucial role in defending the body from pathogenic threats (Magadan et al., 2019), as well as in regulating the composition of resident microbial populations (Belkaid and Hand, 2014). Despite the importance of these distinctive B-cell compartments, relatively little is known about the structure of their antibody repertoires (Magadan et al., 2019), and still less about how these repertoires change with age.

As the site of the greatest microbiota diversity, the intestine is of particular relevance as an important and distinctive immune environment. Previous work on the killifish gut microbiota (Smith et al., 2017) has shown that it declines in alpha diversity and increases in beta diversity with age, patterns that mirror the changes seen in the whole-body composition of the killifish antibody repertoire (Figure 2). Transfer of intestinal content from young to middle-aged fish has also been shown to extend lifespan (Smith et al., 2017). Given these findings, and the intimate relationship between intestinal lymphocytes and gut bacteria (Belkaid and Hand, 2014), we investigated the effect of aging and microbiota transfer on the immune repertoires of gut-resident B-cell populations.

Using intestinal total RNA isolated by Smith et al., 2017, we sequenced the intestinal IGH repertoires of eighteen male GRZ-strain individuals, including four untreated 6-week-old individuals and fourteen 16-week-old individuals from various microbiota-transfer treatment groups (Supplementary file 2b), and investigated the effect of age and treatment condition on repertoire diversity in the killifish intestine.

Contrary to our expectations, neither the alpha nor beta diversity of the killifish intestinal repertoire were significantly affected by microbiota transfer, with no significant difference in clonal diversity, VJ diversity, or RDI distance measures (Figure 4—figure supplements 1–3). In sharp contrast to the whole-body data, however, there was a strong and significant decline in both clonal and VJ alpha diversity with age across all diversity orders (Figure 4B–C, Figure 4—figure supplements 2–3), even without partitioning by clone size. This age-related decline in alpha diversity was consistently far more dramatic than that observed in the whole-body samples at any diversity order. The B-cells of the killifish intestine, therefore, exhibit a much stronger age-dependent decline in repertoire diversity than is seen in the killifish body overall.

Figure 4—figure supplement 1.

Effect of microbiota transfer on the intestinal repertoires of 16-week-old turquoise killifish.

(A–B) Alpha-diversity spectra, indicating average within-individual repertoire diversity for each treatment group and diversity order (n.s.: p > 0.05 Kruskal-Wallis permutation test, Appendix 1—note 7). (A) Clonal alpha-diversity spectra. (B) VJ alpha-diversity spectra, all clones. (D) Normalized VJ beta-diversity spectra, indicating between-individual variability in repertoire composition for each treatment group and diversity order. (E) Distribution of pairwise repertoire dissimilarity index (RDI) distances between killifish intestinal repertoires of different treatment groups (no significant difference between any two groups, Mann-Whitney U tests for pairwise differences). Each curve in (A–C) represents the mean across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

Figure 4—figure supplement 3.

p-Values of Kruskal-Wallis permutation tests (Appendix 1—note 7) for (left) an effect of microbiota transfer treatment group or (B) an age effect in intestinal killifish IGH repertoires at different Hill diversity orders.

Color indicates type of diversity (clonal vs. VJ) being tested; see main text and Appendix 1—note 7 for more details.

Figure 4.

Aging in killifish intestinal repertoires.

(A) Experimental design. Adult male GRZ-strain turquoise killifish were sacrificed at 6 and 16 weeks’ post-hatching, and total RNA was extracted from the dissected intestine. (B–C) Alpha-diversity spectra, indicating average within-individual repertoire diversity for each age group and diversity order (*: 0.05 ≤ 0.01, **: 0.01≤ p ≤ 0.001, Kruskal-Wallis permutation test, Appendix 1—note 7). (A) Clonal alpha-diversity spectra. (B) VJ alpha-diversity spectra, all clones. (D) Normalized VJ beta-diversity spectra, indicating between-individual variability in repertoire composition for each age group and diversity order. (E) Distribution of pairwise repertoire dissimilarity index (RDI) distances between killifish intestinal repertoires at different ages (***: p ≤ 0.001, Mann-Whitney U tests for pairwise age differences). Each curve in (A–C) represents the mean across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

(A–B) Alpha-diversity spectra, indicating average within-individual repertoire diversity for each treatment group and diversity order (n.s.: p > 0.05 Kruskal-Wallis permutation test, Appendix 1—note 7). (A) Clonal alpha-diversity spectra. (B) VJ alpha-diversity spectra, all clones. (D) Normalized VJ beta-diversity spectra, indicating between-individual variability in repertoire composition for each treatment group and diversity order. (E) Distribution of pairwise repertoire dissimilarity index (RDI) distances between killifish intestinal repertoires of different treatment groups (no significant difference between any two groups, Mann-Whitney U tests for pairwise differences). Each curve in (A–C) represents the mean across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

Clonal (top row) or VJ (bottom row) diversity spectra of the intestines of individual turquoise killifish of different ages. Each curve represents the mean Hill diversity for that individual across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

Color indicates type of diversity (clonal vs. VJ) being tested; see main text and Appendix 1—note 7 for more details.

Figure 4—figure supplement 2.

Individual diversity spectra in killifish intestinal repertoires.

Clonal (top row) or VJ (bottom row) diversity spectra of the intestines of individual turquoise killifish of different ages. Each curve represents the mean Hill diversity for that individual across 2000 bootstrap replicates (Appendix 1—note 7); shaded regions indicate 95% confidence intervals over the same.

While results from beta-diversity spectra showed large increases in beta diversity with age at some diversity orders but not at others (Figure 4D), the median pairwise RDI distance between­ individual gut repertoires increased substantially and significantly with age (Figure 4E and Figure 4—figure supplement 4), suggesting that, as in the whole body, killifish intestinal repertoires become increasingly distinct and individualized as they age.

Figure 4—figure supplement 4.

Principal coordinate analysis (PCoA) of pairwise repertoire dissimilarity index (RDI) distances for each age group in the killifish intestinal dataset (Figure 4E, Supplementary file 2b).

One potential explanation for the stronger age-related drop in alpha diversity of intestinal samples is as a consequence of the constant strong antigen exposure experienced by intestinal B-cells, as a result of their interaction with the gut microbiota. This exposure could drive high levels of antigen-dependent clonal expansion, resulting in a greater loss in repertoire diversity (Caruso et al., 2009). Another explanation, not mutually exclusive with the first, is that the gut has different clone-size distribution relative to the whole body. Unlike the whole-body repertoire, the gut does not include the primary lymphoid organs, and so would be expected to be far less dominated by small, naïve clones. Since the population of large clones appears to be more prone to reductions in diversity with age than that of small clones (Figure 2), the stronger overall age-related diversity loss found in the gut repertoire could be a consequence of this greater relative prevalence of large clones.

Rarefaction analysis of clonal counts in whole-body and intestinal repertoires showed that the latter indeed contained far fewer small clones, resulting in a much higher proportion of large clones (Figure 5A). If this difference in clonal composition, rather than some functional difference between intestinal and other B-cells, is primarily responsible for the apparent difference in aging phenotypes between whole-body and intestinal repertoires, we would expect to find a faster rate of clonal diversity loss during aging in intestinal repertoires at low diversity orders (which are dominated by small clones in whole-body samples), but not at high orders (which are dominated by large clones in both sample types). Similarly, we would expect to find faster loss in intestinal samples of V/J diversity considered over all clones, but not when the V/J diversity calculation is restricted to large clones alone.

Figure 5.

Relative clonal composition and aging phenotypes of whole-body and intestinal repertoires.

(A) Rarefaction analysis of clonal composition of antibody repertoires from whole-body and intestinal samples, showing the average number of small (left, <5 unique sequences) and large (middle, 5 unique sequences) clones for each individual across 20 independent replicates at each sample size, as well as the average proportion of all clones in each repertoire which are large (right). Shaded regions around each line show the region within one standard deviation of the mean value. (B) Boxplots of individual diversity measurements of repertoires from each age group in the whole-body and intestinal datasets, divided by the mean diversity of the youngest age group in each dataset. Fitted curves show the maximum-likelihood prediction of a gamma-distributed generalized linear model of diversity vs. age and sample type for the whole-body and intestinal dataset, relative to the average diversity of the youngest age group in each experiment, testing for a significant effect of sample type on the rate of diversity change with age (Student’s t-test,*: 0.01< p 0.05; ***: p 0.001).

Fitted curves show the maximum-likelihood prediction of a gamma-distributed generalized linear model of diversity vs. age and sample type, testing for a significant effect of sample type on the rate of diversity change with age (Student’s t-test,*: 0.01< p ≤ 0.05; **: 0.01< p ≤ 0.001, ***: p < 0.001).

To test these hypotheses, we normalized the diversity measurements from each dataset by the mean diversity of the youngest group in that dataset, then fit generalized linear models for different diversity orders and methods of measuring diversity (Figure 5B and Figure 5—figure supplement 1), testing for a significant interaction between sample type (i.e. gut vs. whole body) and the effect of age on repertoire diversity. Gut samples exhibited significantly higher rates of age-dependent diversity loss under low-order clonal-diversity or total VJ-diversity measures, that is, those metrics for which clones of all sizes were included in the diversity calculation. Conversely, there was no significant difference in rate of diversity loss between sample types for higher-order clonal-diversity measures, nor for V/J-diversity measures restricted to only large clones, indicating that large clones undergo similar rates of age-dependent diversity loss in both sample types. These results closely match the predictions of the clonal-composition model: large clones in both gut and whole-body samples exhibit similarly strong aging phenotypes, but the higher proportions of large clones in gut samples result in these strong phenotypes manifesting more strongly in the behavior of the repertoire as a whole. It therefore appears that, as in whole-body samples, age-dependent diversity loss in killifish intestinal repertoires is primarily a phenomenon of mature, expanded clones.

Figure 5—figure supplement 1.

Extended boxplots of individual diversity measurements of repertoires from each age group in the whole-body and intestinal datasets, divided in each case by the mean diversity of the youngest age group in that dataset.

Fitted curves show the maximum-likelihood prediction of a gamma-distributed generalized linear model of diversity vs. age and sample type, testing for a significant effect of sample type on the rate of diversity change with age (Student’s t-test,*: 0.01< p ≤ 0.05; **: 0.01< p ≤ 0.001, ***: p < 0.001).

Functional correlates of repertoire diversity in killifish

Early work in killifish identified a number of age-associated phenotypes suggestive of immune decline, including thymic degeneration and increased incidence of lymphoma (Cooper et al., 1983). More recently, comparison of young vs. old killifish intestines found a marked age-related increase in the pathogenicity of the killifish gut microbiome, alongside an increase in expression of inflammatory markers, suggesting a decline in the intestinal immune system’s ability to maintain a healthy microbial community (Smith et al., 2017).

These results suggest that the turquoise killifish undergoes rapid functional immune decline with age. Since repertoire diversity also declines with age, this indicates that markers of functional immune decline are coincident with a reduction in repertoire diversity. These results are consistent with similar findings in humans (de Bourcy et al., 2017). However, in the absence of repertoire diversity data, these results do not necessarily imply a direct association between diversity and immune function in aging killifish.

To investigate the relationship between repertoire diversity and immune function more closely, we utilized previously collected intestinal RNA-seq data from the same cohort of killifish used in our intestinal antibody-repertoire analysis (Smith et al., 2017). Using these data alongside our repertoire diversity calculations, we carried out a differential expression analysis of transcript abundance with respect to repertoire diversity for six different diversity orders, controlling for age (Materials and methods). We then performed gene set enrichment analysis (GSEA) to identify gene ontology (GO) terms associated with higher or lower repertoire diversity, across a variety of diversity orders.

The GSEA identified a number of GO terms related to immune function that were significantly associated with increased repertoire diversity (Figure 6, Figure 6—figure supplements 1–3). Most strikingly, ‘B-cell receptor signaling pathway’ was the most strongly enriched term for all six diversity orders analyzed, often by a substantial margin. ‘B-cell proliferation’ was also consistently highly enriched, showing significant positive enrichment for five diversity orders (all except 1.0) and falling in the top 10 most positively enriched terms for four (Figure 6). Other immune terms that were significantly positively associated with repertoire diversity across at least four diversity orders include ‘leukocyte migration’, ‘lymphocyte activation’, ‘leukocyte differentiation’, and ‘regulation of interleukin-6 production’ (Supplementary file 3a). A decline in repertoire diversity is thus associated with a decline in B-cell immune activity in killifish intestine, supporting a functional role for diversity changes in killifish immunosenescence.

Figure 6.

Top 10 most positively enriched gene ontology (GO) terms associated with each diversity order in turquoise killifish, controlling for age, ranked by normalized enrichment score in descending order (Materials and methods).

Immune terms are highlighted in blue. Terms that are significantly positively enriched for a given diversity order, but not in the top 10, are not shown, even if they fall in the top 10 terms for other orders.

Terms that are significantly negatively enriched for a given diversity order, but not in the top 10, are not shown, even if they fall in the top 10 terms for other orders.

Immune terms are highlighted in blue.

Immune terms are highlighted in blue.

Figure 6—figure supplement 1.

Top 10 most negatively enriched gene ontology (GO) terms associated with each diversity order in turquoise killifish, controlling for age, ranked by normalized enrichment score in ascending order (Materials and methods).

Terms that are significantly negatively enriched for a given diversity order, but not in the top 10, are not shown, even if they fall in the top 10 terms for other orders.

Figure 6—figure supplement 3.

Plot of all significantly negatively enriched gene ontology (GO) terms (FDR-adjusted p-value ≤ 0.05) associated with each diversity order in turquoise killifish, controlling for age, ranked by normalized enrichment score in ascending order (Materials and methods).

Immune terms are highlighted in blue.

Plot of all significantly positively enriched gene ontology (GO) terms (FDR-adjusted p-value ≤ 0.05) associated with each diversity order in turquoise killifish, controlling for age, ranked by normalized enrichment score in descending order (Materials and methods).

Discussion

The turquoise killifish is the shortest-lived vertebrate that can be bred in captivity (Cellerino et al., 2016; Harel and Brunet, 2015), with a median lifespan in the short-lived GRZ strain of about 4 months. Despite this, our findings show that the life of a turquoise killifish provides ample time both to develop a complex, diverse, and individualized IgM heavy-chain repertoire (Figure 3A, Figure 1—figure supplements 2–3), and for that repertoire to decline significantly in diversity with age.

These age-associated diversity changes appear to be driven primarily by expanded, antigen-experienced clones, with little observed change in either the diversity of small naïve clones or the entropy of the heavy-chain sequence generation process. This lack of change in small-clone diversity, however, does not necessarily imply that B-cell development is unchanged in aging killifish: it is possible, for example, that a decline in efficiency of B-cell output from primary lymphoid organs is offset by the continuous growth in body size observed throughout the killifish lifespan. Further research into killifish lymphopoiesis will shed light on the relationship between age and the naive B-cell repertoire.

As early as 2009, Caruso et al., 2009, hypothesized that the mucosal adaptive immune system might exhibit particularly strong loss of diversity with age. In what is, to our knowledge, the first published test of this hypothesis, we sequenced the heavy-chain repertoires of isolated killifish gut samples, finding that they do indeed exhibit particularly strong diversity changes with age. However, this difference between the gut and whole-body repertoires appears to result from a difference in clonal composition, rather than in the behavior of any particular clonal subset, suggesting this difference may have less to do with the specifics of the mucosal environment than the location of the primary lymphoid organs. Whatever its source, this age-dependent loss of mucosal repertoire diversity could have important consequences for the gut’s capacity to respond to novel antigens. Future investigation of immune-repertoire aging in a wider variety of mucosal and non-mucosal organs will help disentangle the effects of spatial context on adaptive immunosenescence and provide a clearer picture of the impact of mucosal microbiota.

While our results demonstrate that killifish repertoire diversity declines rapidly with age, the effects on immune function are less clear. Gene expression data from our intestinal cohort indicates that greater intestinal repertoire diversity is associated with gene expression changes indicating greater B-cell receptor signaling activity, lymphocyte activation, and defense responses, suggesting that the decline in diversity seen with age is associated with a decline in immune function. While not necessarily causal, these associations support the biological relevance of repertoire diversity as a metric of immune function. Nevertheless, future experiments should directly investigate the causal association between repertoire diversity and immune function in killifish.

Apart from the nervous system itself, no other system in the vertebrate body exhibits such complex learning and memory behavior as the adaptive immune system. The age-related decline in the functionality of this system is a major cause of mortality and morbidity in the elderly. Our results firmly establish the value of the turquoise killifish as a model for investigating this important and complex process, and demonstrate the importance of studying immune aging in compartments other than peripheral blood. Future experiments in this system have the potential to greatly expand our knowledge of the mechanisms, spatial distribution, and temporal progression of immune-repertoire aging, with potentially vital implications for the future treatment of immunosenescent phenotypes.

Materials and methods

Fish husbandry and sample preparation

Male turquoise killifish (N. furzeri, GRZ-AD strain) from a single hatching cohort were raised under standard husbandry conditions (Dodzian et al., 2018) and housed from 4 weeks’ post-hatching in individual 2.8 l tanks connected to a water-recirculation system. Fish received 12 hr of light per day on a regular light/dark cycle, and were fed bloodworm larvae and brine shrimp nauplii twice a day during the week and once a day during the weekend (Smith et al., 2017; Dodzian et al., 2018).

After being sacrificed in 1.5 g/l tricaine solution at room temperature tank water (Carter et al., 2010), fish (Supplementary file 2c) were flash-frozen in liquid nitrogen and ground to a homogenous powder with a pestle in a liquid-nitrogen-filled mortar. The powder was mixed thoroughly and stored at –80°C prior to RNA isolation. Intestinal total RNA for the gut experiments was provided by Smith et al., 2017.

Immunoglobulin sequencing

Total RNA from whole-body killifish samples was isolated using QIAzol lysis reagent (QIAGEN, 1 ml of reagent per 0.1 g of homogenized tissue) and isopropanol precipitation; gut RNA from microbiota-transfer experiments (Smith et al., 2017) was already prepared and available. Quantification of RNA samples was performed with the Qubit 2.0 fluorometer (Thermo Fisher), while quality control and integrity measurement was performed using the TapeStation 4200 (Agilent).

Reverse transcription and template switching for library preparation was performed on total RNA samples using SMARTScribe Reverse Transcriptase, in line with the protocol specified in Turchaninova et al., 2016; Appendix 1—note 7. The reaction product was purified using SeraSure SPRI beads (Appendix 1—note 7), then underwent three successive rounds of PCR, each of which was followed by a further round of bead purification. The first of these PCR reactions added a second strand to the reverse-transcribed cDNA and amplified the resulting DNA molecules; the second added partial Illumina sequencing adapters and further amplified the library, and the third added complete Illumina adapters, including i5 and i7 indices.

The concentration of each library was then quantified and the libraries were pooled in equimolar ratio, concentrated using SeraSure beads, and size-selected with the BluePippin (Sage Science) to obtain a purified amplicon band. Finally, following a final round of quality control, the pooled and size-selected libraries were sequenced on an Illumina MiSeq System (MiSeq Reagent Kit v3, 2 × 300 bp reads, 30% PhiX spike-in), either at the Cologne Center for Genomics (whole-body libraries) or with Admera Health (intestinal libraries).

Data processing and analysis of repertoire data

Pre-processing of raw sequencing data (including quality filtering, consensus-read generation, and clonotyping) was performed using the pRESTO (Vander Heiden et al., 2014) and Change-O (Gupta et al., 2015) suites of command-line tools (Appendix 1—note 7, Appendix 1—figure 1). Downstream analysis of processed data, including diversity-spectrum inference (Appendix 1—note 7), RDI computation, GLM fitting and rarefaction, was performed in R, as was figure generation and all statistical tests. Generative model inference was performed using IGoR (Marcou et al., 2018). Snakemake (Köster and Rahmann, 2012) was used to design and run data-processing pipelines.

Appendix 1—figure 1.

Summary of pre-processing pipeline applied to killifish repertoire-sequencing data (Appendix 1—note 6).

Functional analysis of RNA-seq data

Intestinal RNA-seq data for gut cohort killifish (Smith et al., 2017) were obtained from SRA (BioProject accession PRJNA379208, Supplementary file 2d). Reads were mapped to the turquoise-killifish genome (Reichwald et al., 2015) with STAR (Dobin et al., 2013), using standard parameters, to compute raw read counts for each transcript and each individual. Read counts were normalized using DESeq2’s default median-of-ratios method (Love et al., 2014). DESeq2 was then used to carry out differential expression analysis based on a generalized linear model, predicting abundance of each transcript in each individual given that individual’s age and repertoire diversity (as calculated above). This analysis was repeated for each of six diversity orders (0, 1, 1.5, 2, 3, and 4).

Killifish transcripts were mapped to human orthologues with BioMart (Durinck et al., 2009; Durinck et al., 2005). In cases where multiple killifish transcripts mapped to a single human transcript, the individual fold change estimates produced by DESeq2 for the killifish transcripts were replaced by a single mean value. Transcripts were then ranked by fold change in descending order, and this ranked list was used as input for GSEA using ClusterProfiler’s gseaGO function (Wu et al., 2021; Yu et al., 2012; Subramanian et al., 2005; Mootha et al., 2003), using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995) to adjust for multiple comparisons and with a significance threshold of 0.05. This produced a list of GO terms (Gene Ontology Consortium, 2021; Ashburner et al., 2000) significantly enriched with respect to repertoire diversity, controlling for age. Redundant GO terms were summarized using ClusterProfiler’s simplify function, with a similarity cutoff of 0.7.

Immune-associated GO terms were identified by descent from one of a small set of high-level immune-associated terms (Supplementary file 3b), which were identified manually. Terms descended from these manually selected ancestor terms were identified using the GO function GOBPOFFSPRING (Gene Ontology Consortium, 2021; Ashburner et al., 2000); any such descendant term was designated as immune-associated.

Data and code availability

Raw data used in these analyses is available via NCBI (BioProject accession PRJNA662612). Processed data and code are available at https://github.com/willbradshaw/killifish-igseq/, (copy archived at swh:1:rev:2c933de6564c1055cb363389778f86bfa3fe4ab2; Bradshaw, 2022).

This study introduces the killifish as a short-lived vertebrate model for immune aging and immunosenescence and characterizes the changes in the immune-repertoire during aging. This work provides an important first step in understanding how aging impacts the immune system in this model organism and will set the stage for many future studies.

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Antibody repertoire sequencing reveals systemic and mucosal immunosenescence in the short-lived turquoise killifish" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, including Matt Kaeberlein as the Reviewing Editor and Reviewer #2, and the evaluation has been overseen by a Senior Editor.

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

This is a very interesting study introducing the killifish as a potential model for immune aging and immunosenescence and characterizing the changes in age-associated immune-repertoire. The authors convincingly show a decrease in diversity of the large expanded B-cell clones that is greater than small clones and a more pronounced change in the intestinal antibody repertoire with age. A limitation of the current study is its descriptive nature and lack of mechanistic insight or strong evidence that aging killifish truly experience functional immunosenescence. We have a few suggestions to potentially enhance the impact of this work that we would like the authors to consider and respond to:

1. Addition of functional data showing a decline in adaptive immunity that goes along with the loss of diversity in the antibody repertoire or citation and discussion of prior literature supporting this in killifish. As it is, it is difficult to know the extent to which the observed changes are strongly correlated with changes in immune function.

2. Whole genome sequencing of lymphoid tissues and brain as a control, from the same old fish to determine whether there are clonal somatic mutations. If confirmed, it may be an important finding, as it would mean that clonal expansions emerge as fast as the killifish lifespan, and it would be a great model to study mechanisms of mutation accumulation and clonal selection with age. This WGS data may be further used to reconstruct immunoglobulin repertoires to understand if the whole-body decrease is driven solely by intestine B cells, or it initiates in lymphoid tissues.

3. RNA sequencing of intestine samples or spleen from young versus old killifish to obtain insights into possible molecular mechanisms clonal expansion and diversity loss. Spleen RNA sequencing may be used to reconstruct the immunoglobulin repertoire. The authors used 750 ng of total RNA in the current study, so there should be enough material for RNA sequencing. Or single cell RNA sequencing may be performed.

While the lack of functional or mechanistic data does not necessarily preclude publication in eLife, the manuscript as is currently overstates the demonstrated importance of this phenomenon. At a minimum, it should be be explicitly noted that further research is needed to determine whether this actually represents immune senescence or simply changes that are of unknown consequence.

Reviewer #2 (Recommendations for the authors):

This is a very interesting study introducing the killifish as a potential model for immune aging and immunosenescence and characterizing the changes in age-associated immune-repertoire. The authors convincingly show a decrease in diversity of the large expanded B-cell clones that is greater than small clones and a more pronounced change in the intestinal antibody repertoire with age. The biggest weakness with the current study is its descriptive nature and lack of strong evidence that these animals truly experience functional immunosenescence. The impact of this work could be strengthened by functional data showing a decline in adaptive immunity that goes along with the loss of diversity in the antibody repertoire or citation and discussion of prior literature supporting this in killifish. As it is, it is difficult to know the extent to which the observed changes are strongly correlated with changes in immune function. While the lack of functional data does not necessarily preclude publication in eLife, the manuscript as is currently overstates the demonstrated importance of this phenomenon. It should at least be explicitly noted that further research is needed to determine whether this actually represents immune senescence or simply changes that are of unknown consequence.

Essential revisions:

This is a very interesting study introducing the killifish as a potential model for immune aging and immunosenescence and characterizing the changes in age-associated immune-repertoire. The authors convincingly show a decrease in diversity of the large expanded B-cell clones that is greater than small clones and a more pronounced change in the intestinal antibody repertoire with age. A limitation of the current study is its descriptive nature and lack of mechanistic insight or strong evidence that aging killifish truly experience functional immunosenescence. We have a few suggestions to potentially enhance the impact of this work that we would like the authors to consider and respond to:

1. Addition of functional data showing a decline in adaptive immunity that goes along with the loss of diversity in the antibody repertoire or citation and discussion of prior literature supporting this in killifish. As it is, it is difficult to know the extent to which the observed changes are strongly correlated with changes in immune function.

These points are well taken. While our initial submission demonstrates that the diversity of the killifish repertoire declines with age, it is true that this does not necessarily imply that this decline is linked to changes in immune functionality.

To provide functional insights into the transcriptomic signature associated with different antibody diversity orders, we now include an analysis linking repertoire diversity data in our intestinal cohort to pre-existing intestinal RNA-seq data from the same individuals (Figure 6). The combination of these two data sets allows us to analyse changes in gene expression with respect to intestinal antibody diversity, controlling for age. We find that a number of immune-activity GO terms – including “B cell receptor signaling pathway”, “B cell proliferation”, and “lymphocyte activation” are significantly positively enriched with respect to repertoire diversity across multiple diversity orders. A decline in intestinal antibody diversity – as seen in ageing – is thus associated with a decline in B-cell immune activity in killifish.

We acknowledge that confident demonstration of a causal link between repertoire diversity and immune state will require experimental challenge of host immunity, for example through infection experiments – something we will address in the future and is beyond the scope of this work. However, we believe these new data are sufficient to demonstrate a significant association between the two, supporting the biological relevance of the age-associated decline in diversity we observe.

2. Whole genome sequencing of lymphoid tissues and brain as a control, from the same old fish to determine whether there are clonal somatic mutations. If confirmed, it may be an important finding, as it would mean that clonal expansions emerge as fast as the killifish lifespan, and it would be a great model to study mechanisms of mutation accumulation and clonal selection with age. This WGS data may be further used to reconstruct immunoglobulin repertoires to understand if the whole-body decrease is driven solely by intestine B cells, or it initiates in lymphoid tissues.

We agree that further investigation of primary repertoire development in killifish lymphoid organs would be a valuable direction for future work, and would help disentangle whole-body from intestine-specific repertoire changes. However, we believe our current analysis is sufficient to demonstrate the presence of clonal somatic mutations in the whole-body repertoire. The pRESTO/Change-O pipeline used in our analysis can distinguish heavy-chain sequences arising from different naive ancestors, and the presence of large clones in the killifish repertoire (see e.g. Supplemental Figure 5A) necessitates rapid clonal expansion.

Ongoing work in our group is indeed directed at studying somatic DNA sequence variation across tissues during aging in killifish, including alternative experimental approaches to investigating killifish repertoire aging. We have now added a sentence about these further research directions to the manuscript discussion. However, we feel these further experiments may be beyond the specific scope of the present work, which is focused on high-level changes in killifish antibody repertoire composition with age.

3. RNA sequencing of intestine samples or spleen from young versus old killifish to obtain insights into possible molecular mechanisms clonal expansion and diversity loss. Spleen RNA sequencing may be used to reconstruct the immunoglobulin repertoire. The authors used 750 ng of total RNA in the current study, so there should be enough material for RNA sequencing. Or single cell RNA sequencing may be performed.

We thank the reviewer for these suggestions. We certainly agree that investigation of repertoire aging in a wider array of immune organs, including spleen, would be highly valuable, and that killifish is a promising model organism in which to carry out these investigations. We have now included analysis of RNA-sequencing data from the killifish gut, which as discussed above supports an association between loss of repertoire diversity and immune function in that organ (see response to A.1). We hope for future work to more comprehensively explore the landscape of organ-specific repertoire ageing in the turquoise killifish; however, we feel that this would be beyond the scope of the present study.

While the lack of functional or mechanistic data does not necessarily preclude publication in eLife, the manuscript as is currently overstates the demonstrated importance of this phenomenon. At a minimum, it should be be explicitly noted that further research is needed to determine whether this actually represents immune senescence or simply changes that are of unknown consequence.

We hope our new analyses and the rewriting of the manuscript address these major points.

Reviewer #2 (Recommendations for the authors):

This is a very interesting study introducing the killifish as a potential model for immune aging and immunosenescence and characterizing the changes in age-associated immune-repertoire. The authors convincingly show a decrease in diversity of the large expanded B-cell clones that is greater than small clones and a more pronounced change in the intestinal antibody repertoire with age.

We thank the reviewer for their supportive assessment of our work!

The biggest weakness with the current study is its descriptive nature and lack of strong evidence that these animals truly experience functional immunosenescence. The impact of this work could be strengthened by functional data showing a decline in adaptive immunity that goes along with the loss of diversity in the antibody repertoire or citation and discussion of prior literature supporting this in killifish. As it is, it is difficult to know the extent to which the observed changes are strongly correlated with changes in immune function. While the lack of functional data does not necessarily preclude publication in eLife, the manuscript as is currently overstates the demonstrated importance of this phenomenon. It should at least be explicitly noted that further research is needed to determine whether this actually represents immune senescence or simply changes that are of unknown consequence.

We agree that our original submission did not sufficiently address the question of functional relevance of an age-related decline in repertoire diversity. Previous work has broadly indicated an age-related immune decline in killifish, and we have now referenced and discussed that work more clearly in our manuscript. However, this is not sufficient to show that an age-related decline in repertoire diversity, as we observe, is per se linked to immune dysfunction.

To address this point, we now include an analysis linking repertoire diversity data in our intestinal cohort to pre-existing intestinal RNA-seq data from the same individuals. The combination of these two data sets allows us to analyse changes in gene expression with respect to intestinal antibody diversity, controlling for age. We find that a number of immune-activity GO terms – including “B cell receptor signaling pathway”, “B cell proliferation”, and “lymphocyte activation” are significantly positively enriched with respect to repertoire diversity across multiple diversity orders. A decline in intestinal antibody diversity – as seen in ageing – is thus associated with a decline in B-cell immune activity in that organ (Figure 6).

Further work in this area should investigate the relationship between diversity and immune function in other organs, as well as investigating whether these connections are causally linked to altered response to pathogens. We have edited the discussion to make these future research needs clear. However, we believe these results are sufficient to demonstrate a meaningful relationship between repertoire diversity and immune function.