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SummaryThe study of bacteria has yielded fundamental insights into cellular biology and physiology, biotechnological advances and many therapeutics. Yet due to a lack of suitable tools, the significant portion of bacterial diversity held within the candidate phyla radiation (CPR) remains inaccessible to such pursuits. Here we show that CPR bacteria belonging to the phylum Saccharibacteria exhibit natural competence. We exploit this property to develop methods for their genetic manipulation, including the insertion of heterologous sequences and the construction of targeted gene deletions. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth and a transposon insertion sequencing genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their Actinobacteria hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strainSouthlakia epibionticumand its corresponding host,Actinomyces israelii, as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

Glutathione (GSH) is an abundant metabolite that can act as a signal, a nutrient source, or serve in a redox capacity for intracellular pathogens. For Francisella, GSH is thought to be a critical in vivo source of cysteine; however, the cellular pathways permitting GSH utilization by Francisella differ between strains and have remained poorly understood. Using genetic screening, we discovered a unique pathway for GSH utilization in Francisella spp. Whereas prior work suggested GSH catabolism initiates in the periplasm, the pathway we define consists of a major facilitator superfamily member that transports intact GSH and a previously unrecognized bacterial cytoplasmic enzyme that catalyzes the first step of GSH degradation. Interestingly, we find that the transporter gene for this pathway is pseudogenized in pathogenic Francisella, explaining phenotypic discrepancies in GSH utilization among Francisella spp. and revealing a critical role for GSH in the environmental niche of these bacteria.

Glioblastoma is an aggressive disease with multiple disrupted signaling networks in the same tumor, demanding the development of personalized combination regimens. Using SYstems Genetics Network AnaLysis we analyzed TCGA multiomics datasets for 422 glioblastoma patients to generate a predictive disease network model (gbmSYGNAL). This model seeks to uncover how subsets of mutations causally modulate regulators (transcription factors, miRNAs, etc.) that mechanistically regulate gene modules (“regulons”) associated with disease progression. Using the real-world registry XCELSIOR (NCT03793088), we identified 55 anti-cancer therapies utilized in glioblastoma treatment (N = 354 patients) and associated them with positive or negative regulon activity within individual patients across the TCGA cohort. A median of 12 regulons were targeted by each drug. Interestingly, nilotinib targeted only 5 regulons but they were found to be active in 38% of patients and regulons overactive in >35% of patients were targeted by repurposed anti-cancer drugs including celecoxib, hydroxychloroquine, and tocilizumab. Standard-of-care treatments lomustine and bevacizumab were predicted to be active in only 28% and 23% of patients, respectively. Using gbmSYGNAL, we then prioritized drugs for 12 additional patients from the XCELSIOR registry. Median overactive regulons per patient was 110 (range 55-254) represented by a median 28 molecular targets (range 17-37). Surprisingly, regulons targeted by metformin were predicted to be overactive in all patients. Certain regulons displayed a binary pattern (high “on” activity or completely “off” per patient) including those targeted by pemetrexed, pembrolizumab, and valproic acid while others showed a gradient of activity across patients including selinexor, panobinostat, palbociclib, and alpelisib. Systems biology analysis of commercially available NGS data combined with the XCELSIOR direct patient engagement platform yielded therapeutically actionable insights for glioblastoma patients in real time. Correlation with clinical outcomes is ongoing for ~50 additional patients and will be presented at the meeting.

Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR− and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.

Corals from the northern Red Sea, in particular the Gulf of Aqaba (GoA), have exceptionally high bleaching thresholds approaching >5°C above their maximum monthly mean (MMM) temperatures. These elevated thresholds are thought to be due to historical selection, as corals passed through the warmer Southern Red Sea during re-colonization from the Arabian Sea. To test this hypothesis, we determined thermal tolerance thresholds of GoA versus Central Red Sea (CRS) Stylophora pistillata corals using the Coral Bleaching Automated Stress System (CBASS) to run a series of standardized acute thermal stress assays. Relative thermal thresholds of GoA and CRS corals were indeed similar and exceptionally high (~7°C above MMM). However, absolute thermal thresholds of CRS corals were on average 3°C above those of GoA corals. To explore the mechanistic underpinnings, we determined gene expression response and microbiome dynamics of coral holobiont compartments. Transcriptomic responses differed markedly, with a strong response to the thermal stress in GoA corals versus a remarkably muted response in corals from the CRS. This pattern was recapitulated in the algal symbionts that showed site-specific genetic differentiation. Concomitant to this, a subset of coral and algal genes showed temperature-induced expression in GoA corals, while exhibiting fixed high expression, i.e. front-loading, in CRS corals. Bacterial community composition of GoA corals changed dramatically under heat stress, whereas CRS corals displayed consistent assemblages, indicating distinct microbial response patterns. Our work demonstrates distinct patterns underlying thermal tolerance across spatial scales, even for the same species and ocean basin. We interpret the response of GoA corals as that of a resilient population approaching a tipping point in contrast to a pattern of consistently elevated thermal resistance in CRS corals that cannot further attune. Such response differences suggest distinct thermal tolerance mechanisms that affect the response of coral populations to ocean warming. published

Glioblastoma is a heterogeneous tumor made up of cell states that evolve over time. We modeled tumor evolutionary trajectories during standard-of-care treatment using multimodal single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multimodal data with single cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that regulate subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches in a concurrent, neo-adjuvant, or recurrent setting. Our proof-of-concept work herein provides the basis for the development of a modeling and analytical system that enables single-cell characterization of an individual patient’s tumor and inferred therapeutic vulnerabilities. Although further validation is required, in the form of in vivo studies of these putative druggable targets, our preliminary analysis and results suggest that systems biology techniques can be used to infer and predict therapeutic vulnerabilities that are either selected or induced during standard-of-care treatment. Ultimately, the information gathered from such systematic modeling and analysis of individual tumors may inform clinical treatment in a more targeted manner and enable a rational, tailored precision medicine that accounts for intratumoral cell heterogeneity.

The success of Mycobacterium tuberculosis (Mtb) is largely due to its ability to withstand multiple stresses encountered in the host. Here, we present a data-driven model that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. The model captures the genome-wide distribution of cis-acting gene regulatory elements and the conditional influences of transcription factors at those elements to elicit environment-specific responses. Analysis of transcriptional responses that may be essential for Mtb to survive acidic stress within the maturing macrophage, identified regulatory control by the MtrAB two-component signal system. Using genome-wide transcriptomics as well as imaging studies, we have characterized the MtrAB circuit by tunable CRISPRi knockdown in both Mtb and the non-pathogenic organism, M. smegmatis (Msm). These experiments validated the essentiality of MtrA in Mtb, but not Msm. We identified that MtrA regulates multiple enzymes that cleave cell wall peptidoglycan and is required for efficient cell division. Moreover, our results suggest that peptidoglycan cleavage, regulated by MtrA, is necessary for Mtb to survive intracellular stress. Further, we present MtrA as an attractive drug target, as even weak repression of mtrA results in loss of Mtb viability and completely clears the bacteria with low-dose isoniazid or rifampicin treatment.

Glioblastoma (GBM) is a heterogeneous tumor made up of cell states that evolve over time. Here, we modeled tumor evolutionary trajectories during standard-of-care treatment using multi-omic single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multi-omic data with single-cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that modulate cell state transitions across subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches to an individual patient in a concurrent, adjuvant, or recurrent setting.

Glioblastoma (GBM) is a heterogeneous tumor made up of cell states that evolve over time. Here, we modeled tumor evolutionary trajectories during standard-of-care treatment using multimodal single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multimodal data with single cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that regulate subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches in a concurrent, neo-adjuvant, or recurrent setting.SummaryInference of mechanistic drivers of therapy-induced evolution of glioblastoma at single cell resolution using RNA-seq and ATAC-seq from patient samples and model systems undergoing standard-of-care treatment informs strategy for identification of tumor evolutionary trajectories and possible cell state-directed therapeutics.

Corals from the northern Red Sea, in particular the Gulf of Aqaba (GoA), have exceptionally high bleaching thresholds approaching >5°C above their maximum monthly mean (MMM) temperatures. These elevated thresholds are thought to be due to historical selection, as corals passed through the warmer Southern Red Sea during re-colonization from the Arabian Sea. To test this hypothesis, we determined thermal tolerance thresholds of GoA versus Central Red Sea (CRS) Stylophora pistillata corals using the Coral Bleaching Automated Stress System (CBASS) to run a series of standardized acute thermal stress assays. Relative thermal thresholds of GoA and CRS corals were indeed similar and exceptionally high (~7°C above MMM). However, absolute thermal thresholds of CRS corals were on average 3°C above those of GoA corals. To explore the mechanistic underpinnings, we determined gene expression response and microbiome dynamics of coral holobiont compartments. Transcriptomic responses differed markedly, with a strong response to the thermal stress in GoA corals versus a remarkably muted response in corals from the CRS. This pattern was recapitulated in the algal symbionts that showed site-specific genetic differentiation. Concomitant to this, a subset of coral and algal genes showed temperature-induced expression in GoA corals, while exhibiting fixed high expression, i.e. front-loading, in CRS corals. Bacterial community composition of GoA corals changed dramatically under heat stress, whereas CRS corals displayed consistent assemblages, indicating distinct microbial response patterns. Our work demonstrates distinct patterns underlying thermal tolerance across spatial scales, even for the same species and ocean basin. We interpret the response of GoA corals as that of a resilient population approaching a tipping point in contrast to a pattern of consistently elevated thermal resistance in CRS corals that cannot further attune. Such response differences suggest distinct thermal tolerance mechanisms that affect the response of coral populations to ocean warming.

Though Clostridioides difficile is among the most studied anaerobes, we know little about the systems level interplay of metabolism and regulation that underlies its ability to negotiate complex immune and commensal interactions while colonizing the human gut. We have compiled publicly available resources, generated through decades of work by the research community, into two models and a portal to support comprehensive systems analysis of C. difficile. First, by compiling a compendium of 148 transcriptomes from 11 studies we have generated an Environment and Gene Regulatory Influence Network (EGRIN) model that organizes 90% of all genes in the C. difficile genome into 297 high quality modules based on evidence for their conditional co-regulation by at least 120 transcription factors. EGRIN predictions, validated with independently-generated datasets, have recapitulated previously characterized C. difficile regulons of key transcriptional regulators, refined and extended membership of genes within regulons, and implicated new genes for sporulation, carbohydrate transport and metabolism. Findings further predict pathogen behaviors in in vivo colonization, and interactions with beneficial and detrimental commensals. Second, by advancing a constraints-based metabolic model, we have discovered that 15 amino acids, diverse carbohydrates, and 24 genes across glyoxylate, Wood-Ljungdahl, nucleotide, amino acid, and carbohydrate metabolism are essential to support growth of C. difficile within an intestinal environment. Models and supporting resources are accessible through an interactive web portal (http://networks.systemsbiology.net/cdiff-portal/) to support collaborative systems analyses of C. difficile.

Our findings demonstrate conclusively that low abundance and upregulated transcripts are preferentially translated, potentially by environment-specific translation systems with distinct ribosomal protein composition. We show that a complex interplay of transcriptional and posttranscriptional regulation underlies the conditional and modular regulatory programs that generate ribosomes of distinct protein composition. The modular regulation of ribosomal proteins with other transcription, translation, and metabolic genes is generalizable to bacterial and eukaryotic microbes. These findings are relevant to how microorganisms adapt to unfavorable environments when they transition from active growth to quiescence by generating proteins from upregulated transcripts that are in considerably lower abundance relative to transcripts associated with the previous physiological state. Selective translation of transcripts by distinct ribosomes could form the basis for adaptive evolution to new environments through a modular regulation of the translational systems., When organisms encounter an unfavorable environment, they transition to a physiologically distinct, quiescent state wherein abundant transcripts from the previous active growth state continue to persist, albeit their active transcription is downregulated. In order to generate proteins for the new quiescent physiological state, we hypothesized that the translation machinery must selectively translate upregulated transcripts in an intracellular milieu crowded with considerably higher abundance transcripts from the previous active growth state. Here, we have analyzed genome-wide changes in the transcriptome (RNA sequencing [RNA-seq]), changes in translational regulation and efficiency by ribosome profiling across all transcripts (ribosome profiling [Ribo-seq]), and protein level changes in assembled ribosomal proteins (sequential window acquisition of all theoretical mass spectra [SWATH-MS]) to investigate the interplay of transcriptional and translational regulation in Halobacterium salinarum as it transitions from active growth to quiescence. We have discovered that interplay of regulatory processes at different levels of information processing generates condition-specific ribosomal complexes to translate preferentially pools of low abundance and upregulated transcripts. Through analysis of the gene regulatory network architecture of H. salinarum, Escherichia coli, and Saccharomyces cerevisiae, we demonstrate that this conditional, modular organization of regulatory programs governing translational systems is a generalized feature across all domains of life. IMPORTANCE Our findings demonstrate conclusively that low abundance and upregulated transcripts are preferentially translated, potentially by environment-specific translation systems with distinct ribosomal protein composition. We show that a complex interplay of transcriptional and posttranscriptional regulation underlies the conditional and modular regulatory programs that generate ribosomes of distinct protein composition. The modular regulation of ribosomal proteins with other transcription, translation, and metabolic genes is generalizable to bacterial and eukaryotic microbes. These findings are relevant to how microorganisms adapt to unfavorable environments when they transition from active growth to quiescence by generating proteins from upregulated transcripts that are in considerably lower abundance relative to transcripts associated with the previous physiological state. Selective translation of transcripts by distinct ribosomes could form the basis for adaptive evolution to new environments through a modular regulation of the translational systems.

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to their previous therapies. Although many therapies exist with diverse mechanisms of action, it is not yet clear how the differences in MM biology across patients impacts the likelihood of success for existing therapies and those in the pipeline. Therefore, we not only need the ability to predict which patients are at high risk for disease progression, but also a means to understand the mechanisms underlying their risk. We hypothesized that knowledge of the biological networks that give rise to MM, specifically the transcriptional regulatory network (TRN) and the mechanisms by which mutations impact gene regulation, would enable improved predictions of disease progression and actionable insights for treatment. Here we present a method to infer TRNs from multi-omics data and apply it to the generation of a MM TRN that links chromosomal abnormalities and somatic mutations to downstream effects on gene expression via perturbation of transcriptional regulators. We find that 141 genetic programs underlie the disease and that the activity profile of these programs fall into one of 25 distinct transcriptional states. These transcriptional signatures prove to be more predictive of outcomes than do mutations and reveal plausible mechanisms for relapse, including the establishment of an immuno-suppressive microenvironment. Moreover, we observe subtype-specific vulnerabilities to interventions with existing drugs and motivate the development of new targeted therapies that appear especially promising for relapsed refractory MM.

SUMMARYFrequent fluctuations in sulfate availability rendered syntrophic interactions between the sulfate reducing bacteriumDesulfovibrio vulgaris(Dv) and the methanogenic archaeonMethanococcus maripaludis(Mm) unsustainable. By contrast, prolonged laboratory evolution in obligate syntrophy conditions improved the productivity of this community but at the expense of erosion of sulfate respiration (SR). Hence, we sought to understand the evolutionary trajectories that could both increase the productivity of syntrophic interactions and sustain SR. We combined a temporal and combinatorial survey of mutations accumulated over 1000 generations of 9 independently-evolved communities with analysis of the genotypic structure for one community down to the single-cell level. We discovered a high level of parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance of a rare SR+Dvlineage within many evolution lines. An in-depth investigation revealed that synergistic epistasis acrossDvandMmgenotypes had enhanced cooperativity within SR- and SR+ assemblages, allowing their co-existence asr- andK-strategists, respectively.

International audience; We present predictive models for comprehensive systems analysis of Clostridioides difficile, the etiology of pseudomembranous colitis. By leveraging 151 published transcriptomes, we generated an EGRIN model that organizes 90% of C. difficile genes into a transcriptional regulatory network of 297 co-regulated modules, implicating genes in sporulation, carbohydrate transport, and metabolism. By advancing a metabolic model through addition and curation of metabolic reactions including nutrient uptake, we discovered 14 amino acids, diverse carbohydrates, and 10 metabolic genes as essential for C. difficile growth in the intestinal environment. Finally, we developed a PRIME model to uncover how EGRIN-inferred combinatorial gene regulation by transcription factors, such as CcpA and CodY, modulates essential metabolic processes to enable C. difficile growth relative to commensal colonization. The C. difficile interactive web portal provides access to these model resources to support collaborative systems-level studies of context-specific virulence mechanisms in C. difficile.

Adaptive prediction is a capability of diverse organisms, including microbes, to sense a cue and prepare in advance to deal with a future environmental challenge. Here, we investigated the timeframe over which adaptive prediction emerges when an organism encounters an environment with novel structure. We subjected yeast to laboratory evolution in a novel environment with repetitive, coupled exposures to a neutral chemical cue (caffeine), followed by a sublethal dose of a toxin (5-FOA), with an interspersed requirement for uracil prototrophy to counter-select mutants that gained constitutive 5-FOA resistance. We demonstrate the remarkable ability of yeast to internalize a novel environmental pattern within 50–150 generations by adaptively predicting 5-FOA stress upon sensing caffeine. We also demonstrate how novel environmental structure can be internalized by coupling two unrelated response networks, such as the response to caffeine and signaling-mediated conditional peroxisomal localization of proteins.

Microbial populations can withstand, overcome and persist in the face of environmental fluctuation. Previously, we demonstrated how conditional gene regulation in a fluctuating environment drives dilution of condition-specific transcripts, causing a population of Desulfovibrio vulgaris Hildenborough (DvH) to collapse after repeatedly transitioning from sulfate respiration to syntrophic conditions with the methanogen Methanococcus maripaludis. Failure of the DvH to successfully transition contributed to the collapse of this model community. We investigated the mechanistic basis for loss of robustness by examining whether conditional gene regulation altered heterogeneity in gene expression across individual DvH cells. We discovered that robustness of a microbial population across environmental transitions was attributable to the retention of cells in two states that exhibited different condition-specific gene expression patterns. In our experiments, a population with disrupted conditional regulation successfully alternated between cell states. Meanwhile, a population with intact conditional regulation successfully switched between cell states initially, but collapsed after repeated transitions, possibly due to the high energy requirements of regulation. These results demonstrate that the survival of this entire model microbial community is dependent on the regulatory system's influence on the distribution of distinct cell states among individual cells within a clonal population.

Diatoms are important primary producers in the ocean that thrive in diverse and dynamic environments. Their survival and success over changing conditions depend on the complex coordination of gene regulatory processes. Here we present an integrated analysis of all publicly available microarray data for the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum. This resource includes shared expression patterns, gene functions, and cis-regulatory DNA sequence motifs in each species that are statistically coordinated over many experiments. These data illustrate the coordination of transcriptional responses in diatoms over changing environmental conditions. Responses to silicic acid depletion segregate into multiple distinctly regulated groups of genes, regulation by heat shock transcription factors (HSFs) is implicated in the response to nitrate stress, and distinctly coordinated carbon concentrating, CO2 and pH-related responses are apparent. Fundamental features of diatom physiology are similarly coordinated between two distantly related diatom species, including the regulation of photosynthesis, cellular growth functions and lipid metabolism. These integrated data and analyses can be explored publicly (http://networks.systemsbiology.net/diatom-portal/).

High representation by ammonia-oxidizing archaea (AOA) in marine systems is consistent with their high affinity for ammonia, efficient carbon fixation, and copper (Cu)-centric respiratory system. However, little is known about their response to nutrient stress. We therefore used global transcriptional and proteomic analyses to characterize the response of a model AOA, Nitrosopumilus maritimus SCM1, to ammonia starvation, Cu limitation and Cu excess. Most predicted protein-coding genes were transcribed in exponentially growing cells, and of ~74% detected in the proteome, ~6% were modified by N-terminal acetylation. The general response to ammonia starvation and Cu stress was downregulation of genes for energy generation and biosynthesis. Cells rapidly depleted transcripts for the A and B subunits of ammonia monooxygenase (AMO) in response to ammonia starvation, yet retained relatively high levels of transcripts for the C subunit. Thus, similar to ammonia-oxidizing bacteria, selective retention of amoC transcripts during starvation appears important for subsequent recovery, and also suggests that AMO subunit transcript ratios could be used to assess the physiological status of marine populations. Unexpectedly, cobalamin biosynthesis was upregulated in response to both ammonia starvation and Cu stress, indicating the importance of this cofactor in retaining functional integrity during times of stress.

The ribosome is a defining structure of all cellular organisms and represents the uniquely biological process of translation. Although ribosomes are typically represented as molecular assembly lines that constitutively perform coded protein synthesis, translation is a system property that emerges from interactions among diverse types of cellular components, including different classes of RNAs, proteins, and amino acids. The prevailing view that all ribosomes within a cell are structurally identical and functionally equivalent was challenged long ago, and is becoming increasingly less tenable with modern experimental tools. Through analysis of environmental and gene regulatory influence networks of H. salinarum, E. coli, and S. cerevisiae, we have discovered a generalized pattern of extensive, environment-specific modularity and heterogeneity in translational subsystems across these representative organisms from each of the three domains of life (Archaea, Bacteria and Eukarya). Systems analysis of H. salinarum growth-associated changes in total mRNA abundance (RNA-seq), ribosome associated transcripts (ribosome profiling), and protein abundance (SWATH-MS proteomics) further support the hypothesis that ribosomes are less of a singular entity, and more of a mosaic patchwork. These data provide evidence that variability in translational subsystems might confer intrinsic regulation of protein synthesis by selectively translating subsets of the transcriptome. We discuss the implication of linked translation-transcription modules as a minimal set of molecules for steering physiological state transitions, as well as acting as a fundamental constraint on biological evolution.

Managing trade‐offs through gene regulation is believed to confer resilience to a microbial community in a fluctuating resource environment. To investigate this hypothesis, we imposed a fluctuating environment that required the sulfate‐reducer Desulfovibrio vulgaris to undergo repeated ecologically relevant shifts between retaining metabolic independence (active capacity for sulfate respiration) and becoming metabolically specialized to a mutualistic association with the hydrogen‐consuming Methanococcus maripaludis. Strikingly, the microbial community became progressively less proficient at restoring the environmentally relevant physiological state after each perturbation and most cultures collapsed within 3–7 shifts. Counterintuitively, the collapse phenomenon was prevented by a single regulatory mutation. We have characterized the mechanism for collapse by conducting RNA‐seq analysis, proteomics, microcalorimetry, and single‐cell transcriptome analysis. We demonstrate that the collapse was caused by conditional gene regulation, which drove precipitous decline in intracellular abundance of essential transcripts and proteins, imposing greater energetic burden of regulation to restore function in a fluctuating environment.

Many species have evolved to function as specialized mutualists, often to the detriment of their ability to survive independently. However, there are few, if any, well-controlled observations of the evolutionary processes underlying the genesis of new mutualisms. Here, we show that within the first 1,000 generations of initiating independent syntrophic interactions between a sulfate reducer (Desulfovibrio vulgaris) and a hydrogenotrophic methanogen (Methanococcus maripaludis), D. vulgaris frequently lost the capacity to grow by sulfate respiration, thus losing the primary physiological attribute of the genus. The loss of sulfate respiration was a consequence of mutations in one or more of three key genes in the pathway for sulfate respiration, required for sulfate activation (sat) and sulfate reduction to sulfite (apsA or apsB). Because loss-of-function mutations arose rapidly and independently in replicated experiments, and because these mutations were correlated with enhanced growth rate and productivity, gene loss could be attributed to natural selection, even though these mutations should significantly restrict the independence of the evolved D. vulgaris. Together, these data present an empirical demonstration that specialization for a mutualistic interaction can evolve by natural selection shortly after its origin. They also demonstrate that a sulfate-reducing bacterium can readily evolve to become a specialized syntroph, a situation that may have often occurred in nature.

Methanogens catalyze the critical methane-producing step (called methanogenesis) in the anaerobic decomposition of organic matter. Here, we present the first predictive model of global gene regulation of methanogenesis in a hydrogenotrophic methanogen, Methanococcus maripaludis. We generated a comprehensive list of genes (protein-coding and noncoding) for M. maripaludis through integrated analysis of the transcriptome structure and a newly constructed Peptide Atlas. The environment and gene-regulatory influence network (EGRIN) model of the strain was constructed from a compendium of transcriptome data that was collected over 58 different steady-state and time-course experiments that were performed in chemostats or batch cultures under a spectrum of environmental perturbations that modulated methanogenesis. Analyses of the EGRIN model have revealed novel components of methanogenesis that included at least three additional protein-coding genes of previously unknown function as well as one noncoding RNA. We discovered that at least five regulatory mechanisms act in a combinatorial scheme to intercoordinate key steps of methanogenesis with different processes such as motility, ATP biosynthesis, and carbon assimilation. Through a combination of genetic and environmental perturbation experiments we have validated the EGRIN-predicted role of two novel transcription factors in the regulation of phosphate-dependent repression of formate dehydrogenase—a key enzyme in the methanogenesis pathway. The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions.

The evolutionary success of an organism is a testament to its inherent capacity to keep pace with environmental conditions that change over short and long periods. Mechanisms underlying adaptive processes are being investigated with renewed interest and excitement. This revival is partly fueled by powerful technologies that can probe molecular phenomena at a systems scale. Such studies provide spectacular insight into the mechanisms of adaptation, including rewiring of regulatory networks via natural selection of horizontal gene transfers, gene duplication, deletion, readjustment of kinetic parameters, and myriad other genetic reorganizational events. Here, we will discuss advances in prokaryotic systems biology from the perspective of evolutionary principles that have shaped regulatory networks for dynamic adaptation to environmental change.

Cytochrome c maturation (Ccm) is a post-translational and post-export protein modification process that involves ten (CcmABCDEFGHI and CcdA or DsbD) components in most Gram-negative bacteria. The absence of any of these components abolishes the ability of cells to form cytochrome c, leading in the case of Rhodobacter capsulatus to the loss of photosynthetic proficiency and respiratory cytochrome oxidase activity. Based on earlier molecular genetic studies, we inferred that R. capsulatus CcmF, CcmH, and CcmI interact with each other to perform heme-apocytochrome c ligation. Here, using functional epitope-tagged derivatives of these components coproduced in appropriate mutant strains, we determined protein-protein interactions between them in detergent-dispersed membranes. Reciprocal affinity purification as well as tandem size exclusion and affinity chromatography analyses provided the first biochemical evidence that CcmF, CcmH, and CcmI associate stably with each other, indicating that these Ccm components form a membrane-integral complex. Under the conditions used, the CcmFHI complex does not contain CcmG, suggesting that the latter thio-reduction component is not always associated with the heme ligation components. The findings are discussed with respect to defining the obligatory components of a minimalistic heme-apocytochrome c ligation complex in R. capsulatus.

Facultative phototrophic bacterium Rhodobacter capsulatus DsbA-null mutants are proficient in photosynthesis but are defective in respiration especially in enriched growth medium at 35 degrees C. They also exhibit severe pleiotropic phenotypes extending from motility defects to osmofragility and oxidative stresses. In this work, using a combined proteomics and molecular genetics approach, we demonstrated that the respiratory defect of R. capsulatus DsbA-null mutants originates from the overproduction of the periplasmic protease DegP, which renders them temperature-sensitive for growth. The DsbA-null mutants reverted frequently to overcome this growth defect by decreasing, but not completely eliminating, their DegP activity. In agreement with these findings, we showed that overproduction of DegP abolishes the newly restored respiratory growth ability of the revertants in all growth media. Structural localizations of the reversion mutations in DegP revealed the regions and amino acids that are important for its protease-chaperone activity. Remarkably although R. capsulatus DsbA-null or DegP-null mutants were viable, DegP-null DsbA-null double mutants were lethal at all growth temperatures. This is unlike Escherichia coli, and it indicates that in the absence of DsbA some DegP activity is required for survival of R. capsulatus. Absence of a DegQ protease homologue in some bacteria together with major structural variations among the DegP homologues, including a critical disulfide bond-bearing region, correlates well with the differences seen between various species like R. capsulatus and E. coli. Our findings illustrate the occurrence of two related but distinct periplasmic protease families in bacterial species.

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium responsible for 12 million active cases of tuberculosis (TB) worldwide. The complexity and critical regulatory components of MTB pathogenicity are still poorly understood despite extensive research efforts. In this study, we constructed the first systems-scale map of transcription factor (TF) binding sites and their regulatory target proteins in MTB. We constructed FLAG-tagged overexpression constructs for 206 TFs in MTB, used ChIP-seq to identify genome-wide binding events and surveyed global transcriptomic changes for each overexpressed TF. Here we present data for the most comprehensive map of MTB gene regulation to date. We also define elaborate quality control measures, extensive filtering steps, and the gene-level overlap between ChIP-seq and microarray datasets. Further, we describe the use of TF overexpression datasets to validate a global gene regulatory network model of MTB and describe an online source to explore the datasets.

The cytoplasmic membrane protein CcdA and its homologues in other species, such as DsbD of Escherichia coli , are thought to supply the reducing equivalents required for the biogenesis of c -type cytochromes that occurs in the periplasm of gram-negative bacteria. CcdA - null mutants of the facultative phototroph Rhodobacter capsulatus are unable to grow under photosynthetic conditions (Ps − ) and do not produce any active cytochrome c oxidase (Nadi − ) due to a pleiotropic cytochrome c deficiency. However, under photosynthetic or respiratory growth conditions, these mutants revert frequently to yield Ps + Nadi + colonies that produce c -type cytochromes despite the absence of CcdA. Complementation of a CcdA-null mutant for the Ps + growth phenotype was attempted by using a genomic library constructed with chromosomal DNA from a revertant. No complementation was observed, but plasmids that rescued a CcdA-null mutant for photosynthetic growth by homologous recombination were recovered. Analysis of one such plasmid revealed that the rescue ability was mediated by open reading frame 3149, encoding the dithiol:disulfide oxidoreductase DsbA. DNA sequence data revealed that the dsbA allele on the rescuing plasmid contained a frameshift mutation expected to produce a truncated, nonfunctional DsbA. Indeed, a dsbA ccdA double mutant was shown to be Ps + Nadi + , establishing that in R. capsulatus the inactivation of dsbA suppresses the c -type cytochrome deficiency due to the absence of ccdA . Next, the ability of the wild-type dsbA allele to suppress the Ps + growth phenotype of the dsbA ccdA double mutant was exploited to isolate dsbA -independent ccdA revertants. Sequence analysis revealed that these revertants carried mutations in dsbB and that their Ps + phenotypes could be suppressed by the wild-type allele of dsbB . As with dsbA , a dsbB ccdA double mutant was also Ps + Nadi + and produced c -type cytochromes. Therefore, the absence of either DsbA or DsbB restores c -type cytochrome biogenesis in the absence of CcdA. Finally, it was also found that the DsbA-null and DsbB-null single mutants of R. capsulatus are Ps + and produce c -type cytochromes, unlike their E. coli counterparts, but are impaired for growth under respiratory conditions. This finding demonstrates that in R. capsulatus the dithiol:disulfide oxidoreductases DsbA and DsbB are not essential for cytochrome c biogenesis even though they are important for respiration under certain conditions.

Mycobacterium tuberculosis (MTB) infects 30% of all humans and kills someone every 20–30 s. Here we report genome-wide binding for ~80% of all predicted MTB transcription factors (TFs), and assayed global expression following induction of each TF. The MTB DNA-binding network consists of ~16,000 binding events from 154 TFs. We identify >50 TF-DNA consensus motifs and >1,150 promoter-binding events directly associated with proximal gene regulation. An additional ~4,200 binding events are in promoter windows and represent strong candidates for direct transcriptional regulation under appropriate environmental conditions. However, we also identify >10,000 ‘dormant’ DNA-binding events that cannot be linked directly with proximal transcriptional control, suggesting that widespread DNA binding may be a common feature that should be considered when developing global models of coordinated gene expression., Adaptation of Mycobacterium tuberculosis to the host environment is principally mediated through its transcription factors. Here, the authors report the DNA binding and transcriptional profile of ~80% of all predicted M. tuberculosis transcription factors, and find wide-spread dormant DNA binding.

Background Mycobacterium tuberculosis senses and responds to the shifting and hostile landscape of the host. To characterize the underlying intertwined gene regulatory network governed by approximately 200 transcription factors of M. tuberculosis, we have assayed the global transcriptional consequences of overexpressing each transcription factor from an inducible promoter. Results We cloned and overexpressed 206 transcription factors in M. tuberculosis to identify the regulatory signature of each. We identified 9,335 regulatory consequences of overexpressing each of 183 transcription factors, providing evidence of regulation for 70% of the M. tuberculosis genome. These transcriptional signatures agree well with previously described M. tuberculosis regulons. The number of genes differentially regulated by transcription factor overexpression varied from hundreds of genes to none, with the majority of expression changes repressing basal transcription. Exploring the global transcriptional maps of transcription factor overexpressing (TFOE) strains, we predicted and validated the phenotype of a regulator that reduces susceptibility to a first line anti-tubercular drug, isoniazid. We also combined the TFOE data with an existing model of M. tuberculosis metabolism to predict the growth rates of individual TFOE strains with high fidelity. Conclusion This work has led to a systems-level framework describing the transcriptome of a devastating bacterial pathogen, characterized the transcriptional influence of nearly all individual transcription factors in M. tuberculosis, and demonstrated the utility of this resource. These results will stimulate additional systems-level and hypothesis-driven efforts to understand M. tuberculosis adaptations that promote disease. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0502-3) contains supplementary material, which is available to authorized users.

The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of overexpressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection.

Copper is an essential micronutrient used as a metal cofactor by a variety of enzymes, including cytochrome c oxidase (Cox). In all organisms from bacteria to humans, cellular availability and insertion of copper into target proteins are tightly controlled due to its toxicity. The major subunit of Cox contains a copper atom that is required for its catalytic activity. Previously, we identified CcoA (a member of major facilitator superfamily transporters) as a component required for cbb3-type Cox production in the Gram-negative, facultative phototroph Rhodobacter capsulatus. Here, first we demonstrate that CcoA is a cytoplasmic copper importer. Second, we show that bypass suppressors of a ccoA deletion mutant suppress cbb3-Cox deficiency by increasing cellular copper content and sensitivity. Third, we establish that these suppressors are single-base-pair insertion/deletions located in copA, encoding the major P1B-type ATP-dependent copper exporter (CopA) responsible for copper detoxification. A copA deletion alone has no effect on cbb3-Cox biogenesis in an otherwise wild-type background, even though it rescues the cbb3-Cox defect in the absence of CcoA and renders cells sensitive to copper. We conclude that a hitherto unknown functional interplay between the copper importer CcoA and the copper exporter CopA controls intracellular copper homeostasis required for cbb3-Cox production in bacteria like R. capsulatus., IMPORTANCE Copper (Cu) is an essential micronutrient required for many processes in the cell. It is found as a cofactor for heme-copper containing cytochrome c oxidase enzymes at the terminus of the respiratory chains of aerobic organisms by catalyzing reduction of dioxygen (O2) to water. Defects in the biogenesis and copper insertion into cytochrome c oxidases lead to mitochondrial diseases in humans. This work shows that a previously identified Cu transporter (CcoA) is a Cu importer and illustrates the link between two Cu transporters, the importer CcoA and the exporter CopA, required for Cu homeostasis and Cu trafficking to cytochrome c oxidase in the cell.

The ease of generating high-throughput data has enabled investigations into organismal complexity at the systems level through the inference of networks of interactions among the various cellular components (genes, RNAs, proteins and metabolites). The wider scientific community, however, currently has limited access to tools for network inference, visualization and analysis because these tasks often require advanced computational knowledge and expensive computing resources. We have designed the network portal (http://networks.systemsbiology.net) to serve as a modular database for the integration of user uploaded and public data, with inference algorithms and tools for the storage, visualization and analysis of biological networks. The portal is fully integrated into the Gaggle framework to seamlessly exchange data with desktop and web applications and to allow the user to create, save and modify workspaces, and it includes social networking capabilities for collaborative projects. While the current release of the database contains networks for 13 prokaryotic organisms from diverse phylogenetic clades (4678 co-regulated gene modules, 3466 regulators and 9291 cis-regulatory motifs), it will be rapidly populated with prokaryotic and eukaryotic organisms as relevant data become available in public repositories and through user input. The modular architecture, simple data formats and open API support community development of the portal.

In most anoxygenic phototrophic bacteria, apocytochromes c are synthesized in the cytoplasm, translocated across the membrane and matured to holocytochromes c on the periplasmic side. The extracytoplasmic maturation process requires a complex biogenesis pathway (Ccm-system I) consisting of up to ten components to carry out specific steps. These include translocation and delivery of the heme, chaperoning and thio-oxidoreduction of the apocytochrome c as well as heme ligation steps. Because cytochromes are often part of multi-subunit protein complexes, matured holocytochromes may be assembled into active enzyme complexes. Examples include the ubihydroquinone:cytochrome c oxidoreductase (cytochrome bc 1 complex) or the aa 3- or cbb 3-type cytochrome c oxidases. Assemblies of these complexes are tightly coordinated and often require additional specific biogenesis components. In this chapter, we discuss the maturation process of c-type cytochromes and the assembly pathways of the aa 3- and cbb 3-type cytochrome c oxidases in anoxygenic phototrophic bacteria, with a specific focus on Rhodobacter species.

During cytochrome c maturation (Ccm), the DsbA-dependent thio-oxidative protein-folding pathway is thought to introduce a disulphide bond into the haem-binding motif of apocytochromes c. This disulphide bond is believed to be reduced through a thio-reductive pathway involving the Ccm components CcdA (DsbD), CcmG and CcmH. Here, we show in Rhodobacter capsulatus that in the absence of DsbA cytochrome c levels were decreased and CcdA or CcmG or the putative glutathione transporter CydDC was not needed for Ccm. This decrease was not due to overproduction of the periplasmic protease DegP as a secondary effect of DsbA absence. In contrast, CcmH was absolutely necessary regardless of DsbA, indicating that compensatory thio-redox interactions excluded it. Remarkably, the double (DsbA-CcmG) and triple (DsbA-CcmG-CcdA) mutants produced cytochromes c at lower levels than the DsbA-null mutants, unless they contained a CcmG derivative (CcmG*) lacking its thio-reductive activity. Purified CcmG* can bind apocytochrome c in vitro, revealing for the first time a thiol-independent, direct interaction between apocytochrome c and CcmG. Furthermore, elimination of the thio-redox components does not abolish cytochrome c production, restricting the number of Ccm components essential for haem-apocyt c ligation per se during Ccm.

In all organisms, haem is post-translationally and covalently attached to c apocytochromes to produce c holocytochromes via a process called c-type cytochromes maturation, which involves numerous components. In bacteria it was not clear which of these components catalyses the extracytoplasmic haem-apocytochrome ligation per se. In this issue of Molecular Microbiology, Feissner and colleagues report that a single polypeptide from Helicobacter pylori, corresponding to the fusion of two proteins found in other organisms, performs haem ligation to a coexpressed Bordetella pertussis apocytochrome c in an Escherichia coli mutant lacking its own cytochrome c maturation proteins. This simple experimental system pinpoints the components catalysing extracytoplasmic covalent haem ligation and raises intriguing issues about the requirements for delivery of haem and apocytochrome c substrates to produce c holocytochromes.

A high speed flow cytometric cell sorter was modified to maintain a controlled anaerobic environment. This technology enabled coupling of the precise high-throughput analytical and cell separation capabilities of flow cytometry to the assessment of cell viability of evolved lineages of obligate anaerobic organisms from cocultures.