Adaptations in gut Bacteroidales facilitate stable co-existence with their lytic bacteriophages

Abstract

Bacteriophages (phages) and bacteria within the gut microbiome persist in long-term stable coexistence. These interactions are driven by eco-evolutionary dynamics, where bacteria employ a variety of mechanisms to evade phage infection, while phages rely on counterstrategies to overcome these defenses. Among the most abundant phages in the gut are the crAss-like phages that infect members of the order Bacteroidales, in particular, genus Bacteroides. In this study, we explored some of the mechanisms enabling the co-existence of four phage-Bacteroidales host pairs in vitro using a multi-omics approach (transcriptomics, proteomics and metabolomics). These included three Bacteroides species paired with three crAss-like phages (Bacteroides intestinalis and фcrAss001, Bacteroides xylanisolvens and фcrAss002, and an acapsular mutant of Bacteroides thetaiotaomicron with DAC15), and Parabacteroides distasonis paired with the siphovirus фPDS1. We show that phase variation of individual capsular polysaccharides (CPSs) is the primary mechanism promoting phage co-existence in Bacteroidales, but this is not the only strategy. Alternative resistance mechanisms, while potentially less efficient than CPS phase variation, can be activated to support bacterial survival by regulating gene expression and resulting in metabolic adaptations, particularly in amino acid degradation pathways. These mechanisms, also likely regulated by phase variation, enable bacterial populations to persist in the presence of phages, and vice versa. An acapsular variant of B. thetaiotaomicron demonstrated broader transcriptomic, proteomic, and metabolomic changes, supporting the involvement of additional resistance mechanisms beyond CPS variation. This study advances our understanding of long-term phage-host interaction, offering insights into the long-term persistence of crAss-like phages and extending these observations to other phages, such as фPDS1. Knowledge of the complexities of phage-bacteria interactions is essential for designing effective phage therapies and improving human health through targeted microbiome interventions.

Keywords: Bacteriophages; Bacteroides; Crassvirales; Parabacteroides; co-culture; crassphages; gut microbiome; intestinal microbiota; phage-bacteria interaction; virome.

Figure 1.

Bacteria-phage dynamics and changes in phage resistance during the 5-day co-culture. (a–d) enumeration of bacteria and phage during the 5-day co-culture experiments. After each 24-hour period, a new subculture (SC) was performed in fresh media at a dilution of 1:50. (a) B. intestinalis + ɸcrAss001, (b) B. xylanisolvens + ɸcrAss002, (c) P. distasonis + ɸPDS1, (d) B. thetaiotaomicron Δcps + DAC15. The orange line represents bacterial counts (CFU/mL) for the control condition (uninfected bacteria), the blue line represents bacterial counts (CFU/mL) in co-culture with phage, and the black line represents phage counts (pfu/mL or copies/mL) in co-culture with bacteria. The choice of the phage enumeration method depended on the ability to produce countable plaques with a given phage-host pair (PFU/mL). Non-plaquing ɸcrAss002 and ɸPDS1 were quantified by qPCR (copies/mL). (e-h) changes in the percentage of resistant cells during the 5 days of co-culture experiments. (e) B. intestinalis + ɸcrAss001, (f) B. xylanisolvens + ɸcrAss002, (g) P. distasonis + ɸPDS1, (h) B. thetaiotaomicron Δcps + DAC15. Orange bars represent the mean percentage of resistant cells in the uninfected culture (control), while blue bars show the mean percentage of resistant cells when bacteria were exposed to phage. Error bars indicate standard deviation (SD). All experiments were carried out in triplicate. *: statistically significant differences in bacterial counts or percentage of resistant colonies when comparing the control with the infected conditions were set at p < 0.05.

Figure 2.

Transcriptional changes and CPS expression profiles after bacteria-phage co-culture. (a-d) transcriptional changes during early-log phase growth on the fifth day of each bacteria-phage co-culture: (a) B. intestinalis + ɸcrAss001, (b) B. xylanisolvens + ɸcrAss002, (c) P. distasonis + ɸPDS1, (d) B. thetaiotaomicron Δcps + DAC15. Genes are plotted as dots according to their chromosomal location in each bacterial host. The log₂ fold change represents the differential expressions of genes when comparing control (uninfected) with infected bacteria. Red dots represent genes that were significantly upregulated upon phage infection, blue dots are those that were significantly downregulated, and grey dots are those that did not show statistically significant changes in expression. Gene clusters implicated in capsule biosynthesis are labelled as CPS (capsular polysaccharide) and PVR (phase-variable region). Statistical significance was determined using an FDR-adjusted p-value (FDR < 0.05). (e-g) relative expression of the different CPS loci in bacterial capsular strains under infected and uninfected conditions determined by RNA-seq data. (e) B. intestinalis + ɸcrAss001, (f) B. xylanisolvens + ɸcrAss002, (g) P. distasonis + ɸPDS1. The expression values for each CPS cluster were calculated by averaging the expression levels of their constituent genes, followed by normalization against the total expression of all CPS clusters. The resulting values are presented as a percentage of the total CPS expression for each condition. Differences in the relative expression of the CPS loci were analysed assuming normal distribution using Welch´s t-test. Significant differences in proportions after phage infection are indicated in the legend as follows: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure 3.

Differential proteomics profile in the supernatant obtained during the early-log phase on the fifth day of the co-culture experiment with B. thetaiotaomicron Δcps and DAC15. (a) Principal component analysis (PCA) of proteomic profiles of B. thetaiotaomicron Δcps supernatant between control (orange) and DAC15-infected samples (blue colour). Ellipses represent 95% confidence intervals, and the explained variances of the two principal components are shown in brackets along the axes. (b) volcano plot representing the significantly differentially abundant proteins. Dots represent individual proteins upregulated in control (left) and DAC15 infection (right) conditions. Y-axis shows non-adjusted p-values, however, dots are coloured based on corrected p-values (Benjamini-Hochberg FDR) representing different thresholds: 5% (blue), 10% (green), 20% (red), and non-significant (black). (c) heatmap displaying hierarchical clustering of protein abundance profiles after z-score transformation. Row and columns are clustered based on Euclidean distance, showing differential protein expression between control and infected conditions. Columns are coloured by sample condition with blue representing infected samples and orange representing control. Yellow indicates higher relative protein abundances, while blue represents lower relative abundance.

Figure 4.

Intracellular metabolomic changes in B. thetaiotaomicron Δcps in response to DAC15 infection. (a-b) LC-MS peak intensities of 3-methyl-2-oxovaleric acid (a) and 4-methyl-2-oxovaleric acid (b) for each phage-host pair, obtained from untargeted intracellular metabolomics analysis performed at early-log phase of growth on the fifth day of the co-culture experiment. Bars represent the mean of triplicate biological samples, with error bars indicating the standard deviation (SD). * significant differences were set up at p < 0.05. (c) Principal component analysis (PCA) of intracellular metabolomic profiles from B. thetaiotaomicron Δcps and DAC15 co-cultures, based on compounds detected with accuracy levels 1 and 2a. Orange indicates the control condition (uninfected), while blue is the infected condition. Ellipses represent 95% confidence intervals, and the explained variances of the two principal components are shown in brackets along the axes. (d) important features identified by partial least squares-discriminant analysis (PLS-DA) in B. thetaiotaomicron Δcps bacterial pellets collected at the early-log phase on the fifth day of the co-culture. The coloured boxes on the right indicate the relative peak area of each corresponding metabolite in the groups under study, with red indicating higher peak areas and blue indicating lower. Group 1 corresponds to the control condition, and group 2 corresponds to the DAC15 infected samples. 2-oxo-3-PPA: 2-oxo-3-phenylpropanoic acid; ACC: 1-aminocyclopropanecarboxylic acid.