Biology subjects

Palsson, B. O.

Publications and source records attributed to Palsson, B. O..

At least 19 recordsLinked to original sources

bioRxiv2026

Diversity and evolution of the transcriptional regulatory networks of Pseudomonas strains revealed using machine learning

The genus Pseudomonas consists of diverse and ecologically significant species that form close associations with both plants and animals. This genus is widely studied due to the clinically relevant Pseudomonas aeruginosa, model plant pathogen Pseudomonas syringae, and non-pathogenic, industrially relevant Pseudomonas putida. The different metabolic and physiological capabilities of these species are enabled by their unique genetic makeup as well as varying regulatory mechanisms. To study the transcriptional basis for the diversity of the three species, we applied independent component analysis to strain-specific RNA-seq datasets to identify independently modulated gene sets (iModulons) and their condition-specific activity levels. We then mapped iModulons across strains based on their similarity in orthologous gene membership. Through comparison of iModulon gene membership and activities, we find that: (i) iModulons reveal shared and unique regulatory modalities across strains; (ii) unique adaptations in common functions, such as translation and pyoverdine production/uptake, manifest through both differential iModulon gene membership and condition-specific activation states in each strain; (iii) iModulons facilitate comparison of stress responses at the systems level; and (iv) iModulons highlight unique virulence factor enrichment and host-specific adaptations in human and plant pathogens. Altogether, comparing the modularized transcriptomes of the three strains provides unique and comprehensive insights into their differential evolution. ImportanceClosely related bacterial species often have vastly different metabolic and physiological capabilities, yet the regulatory mechanisms underlying these adaptations remain poorly understood. Here, we compare the transcriptional regulatory networks of three representative Pseudomonas strains through cross-strain iModulon analysis. By comparing both iModulon gene composition and activity across strains, we identify conserved regulatory modules alongside lineage-specific adaptations in functions associated with virulence, translation, iron acquisition, motility, and stress responses. Our results demonstrate that iModulons provide a genome-scale framework for comparing transcriptional regulation across closely related organisms, revealing regulatory innovations that are not apparent from genome comparisons alone. This work establishes a scalable approach for studying the evolution of bacterial transcriptional regulatory networks and the regulatory basis of niche specialization.

systems biology↗

bioRxiv2026

Pangenomic decomposition reveals lineage-specific immune-evasion and virulence architectures in group A Streptococcus

Streptococcus pyogenes (group A Streptococcus, GAS) causes over 700 million infections annually and has resurged globally as a cause of invasive disease. However, the genomic basis by which distinct GAS lineages produce diverse clinical phenotypes remains incompletely understood. Here, we analyzed 399 quality-controlled complete genomes spanning 103 emm types and 27 countries and applied non-negative matrix factorization (NMF) to decompose the GAS pangenome into co-inherited gene modules capturing both clonal lineages and mobile elements. This framework revealed that the deepest division in the accessory genome is not defined by emm type, but by a 27-gene Sda-1-encoding prophage linked to the hypervirulent M1T1 pandemic clone. This NET-degrading module unites emm1, emm12, and emm77 lineages, including fixation in emm77/ST63, extending its distribution beyond classically invasive lineages. Across lineages, virulence determinants segregate into distinct combinations, indicating that invasive disease arises through convergent but mechanistically distinct programs. Consistent with this, highly invasive ST52-emm28 lacks Sda1 and deploys an alternative repertoire. The decomposition also resolves a gene module corresponding to the emm-pattern D regulon associated with skin tropism, linking accessory genome structure to host niche adaptation. We further identify three sequence-divergent speC paralogs on independent prophages. These findings define modular GAS virulence architectures and establish NMF-based pangenome analysis as a framework for genomic surveillance beyond single-locus typing. ImportanceGroup A Streptococcus causes diseases ranging from strep throat to life-threatening flesh-eating infections, with severe cases increasing in recent years and no vaccine currently available. The species is conventionally classified by its M protein gene, but this single-locus system does not capture the extensive genomic diversity driven by prophages that transfer toxin and immune-evasion genes between bacterial lineages. Here, we applied unsupervised machine learning to decompose the pangenome of nearly 400 complete genomes into modules of co-inherited genes. We find that the deepest division among lineages is determined by a prophage carrying a gene that enables evasion of neutrophil extracellular traps, and identify this module at fixation in a lineage not previously known to carry it. We also show that a key toxin gene exists as three independently evolved variants on distinct prophages, and that invasive lineages deploy distinct combinations of virulence factors. This framework enables genomic surveillance based on virulence architecture rather than single-gene typing.

microbiology↗

bioRxiv2025

Deep Red Blood Cell Proteome Defines the Band 3 N-Terminus Interactome as a Regulator of Hypoxic Adaptation via BLVRB-Dependent S-Nitroso Transfer

Red blood cells (RBCs) have long been regarded as passive oxygen carriers, yet growing evidence reveals a complex, dynamic proteome independent of de novo gene expression. Here, we define the erythrocyte as an oxygen-responsive system organized around a Band 3 (SLC4A1)-centered metabolon. Using deep proteomics of ultra-pure RBCs and cross-linking interactomics, we identify biliverdin reductase B (BLVRB) as a previously unrecognized Band 3 interactor that binds the N-terminal cytosolic domain under normoxia and dissociates under hypoxia, when band 3-deoxyhemoglobin interactions increase threefold. This reversible interaction forms an oxygen-sensitive switch coupling structural, redox, and metabolic remodeling. In humanized mice, truncation of the Band 3 N-terminus disrupted glycolytic activation, reduced 2,3-bisphosphoglycerate synthesis, and impaired exercise tolerance despite preserved cardiopulmonary function, establishing the physiological relevance of this module. Population-scale proteome quantitative trait locus (pQTL) analyses revealed coordinated variation of SLC4A1 and BLVRB abundance but minimal association of biliverdin levels with BLVRB genotype, suggesting alternative functions beyond heme catabolism. Mechanistically, BLVRB Cys109 acts as a nitric oxide (NO) relay, trans-nitrosating glycolytic enzymes such as GAPDH at active site Cys152, transiently inhibiting glycolysis. This S-nitrosation-mediated feedback mirrors conserved mechanisms in plants, where GAPDH-SNO redirects carbon flow toward the Calvin-Benson cycle under nitrosative stress, revealing an evolutionary convergence in gas-responsive metabolic control. Collectively, our findings define a Band 3-BLVRB-hemoglobin axis that links oxygen sensing, NO signaling, and redox homeostasis, providing a unifying model for how an anucleate cell achieves environmental adaptability through reversible protein-protein interactions and post-translational chemistry. Graphic abstractIssaian et al. define the most comprehensive proteome of ultra-pure human red blood cells (3,775 proteins) and map the O2-dependent interactome, revealing a Band 3-BLVRB-hemoglobin module that links oxygen sensing to metabolic remodeling via reversible inhibitory S-nitrosation of GAPDH C152. In plants this redirects carbon toward photosynthesis, illustrating a conserved NO-dependent metabolic reprogramming mechanism across oxygen-regulated systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/691178v1_ufig1.gif" ALT="Figure 1"> View larger version (89K): org.highwire.dtl.DTLVardef@122468org.highwire.dtl.DTLVardef@114428dorg.highwire.dtl.DTLVardef@11d40c4org.highwire.dtl.DTLVardef@1870fb7_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDeep proteomics defines a complete, contamination-free RBC proteome (3,775 proteins) C_LIO_LICross-linking proteomics maps an oxygen-sensitive Band 3-centered interactome C_LIO_LIO2-dependent BLVRB-Band 3 binding regulates metabolism via S-nitrosation of GAPDH C_LIO_LIBand 3 N-terminus is required for hypoxic remodeling and exercise tolerance in vivo C_LI

biochemistry↗

bioRxiv2025

Genetic variation of human G6PD impacts Red Blood Cell transfusion efficacy

Glucose-6-phosphate dehydrogenase (G6PD) deficiency, the most common human enzymopathy, affects 6% of the global population, yet its impact on blood storage and transfusion efficacy remains undefined. We integrated genome-metabolome-proteome analyses of 13,091 blood donors (362 G6PD SNPs), validated in a recalled cohort (n=643), linked donor-recipient databases, humanized mouse models (canonical, African A- [V68M+N126D], Mediterranean [S188F]), and a prospective sickle cell disease study. Common G6PD variants reduced protein abundance, reprogrammed redox metabolism, and increased storage hemolysis. In mice, G6PD-deficient RBCs showed lower post-transfusion recovery, higher oxidative stress, and impaired renal oxygenation. Clinically, recipients of G6PD-deficient units exhibited smaller hemoglobin increments and reduced RBC L{superscript 1}Cr-survival (-8% at 24 h; -12% at 4 weeks). Structural studies revealed kinetic fragility for A- and thermodynamic fragility for Med-, linking genotype to protein instability and transfusion outcome. These findings identify donor G6PD genotype as a determinant of transfusion efficacy, supporting genotype-aware inventory-management strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/689741v1_ufig1.gif" ALT="Figure 1"> View larger version (76K): org.highwire.dtl.DTLVardef@1897489org.highwire.dtl.DTLVardef@1420587org.highwire.dtl.DTLVardef@178e8ddorg.highwire.dtl.DTLVardef@1003b44_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Multi-strain Analysis of Pseudomonas putida Reveals the Metabolic and Genetic Diversity of the Species.

Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains. We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a [~]8% increase to the available genomic data for P. putida. Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes such as PcaI and PcaJ revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.

bioengineering↗

bioRxiv2025

QSProteome: A Community-Driven Interactive Platform for Large-Scale Exploration and Evaluation of Predicted Protein Complex Structures.

QSProteome (https://QSProteome.org) is a community-scale platform for modeling, evaluating, and refining quaternary protein structure. The resource hosts 35,528 unique modeled assemblies spanning over 42,000 genes, covering nearly all curated complexes in BioCyc and ComplexPortal databases. Each model is displayed on an interactive page with 3D visualization, chain-level confidence metrics, structural alignments, functional annotations, and automated stoichiometry checks against database expectations. A cloud-based server supports continuous user uploads and automated processing pipelines--enabling submission and validation of >54,000 models within 14 weeks. To promote iterative refinement, QSProteome includes a gamified re-curation workflow that transitions users from training modules into live curation, enabling the community-led assessment of 1,547 ABC transporter complexes. Together, these components form a dynamic, scalable infrastructure for proteome-scale structural biology. By unifying modeling, validation, and annotation in a reusable, searchable, and community-extensible framework, QSProteome enables proteome-scale structure accessibility and reuse--powering discovery, annotation, and collaborative refinement across the structural biology community.

bioinformatics↗

bioRxiv2025

Aerobicity stimulon in Escherichia coli revealed using multi-scale computational systems biology of adapted respiratory variants

Energy homeostasis facilitated by the interplay of substrate-level and oxidative phosphorylation is crucial for bacterial adaptation to diverse substrates and environments. To investigate how bioenergetic systems optimize under restrictive conditions, we evolved ETS variants with distinct proton-pumping efficiencies (1, 2, 3, or 4 proton(s) per electron) on succinate and glycerol. These substrates impose unique metabolic constraints: succinate requires complete gluconeogenesis, while glycerol supports mixed glycolytic and gluconeogenic fluxes. Multi-scale computational analysis of the strains revealed (a) Growth optimization across carbon substrates for multiple ETS variants, (b) A conserved aerobicity stimulon comprising seven independently regulated gene groups that are co-regulated with increasing aerobic capacities, (c) Proteome reallocation linked to aerobicity, validated using genome-scale metabolism and expression modeling, and (d) Carbon source-specific compensatory mutations in succinate transporters and regulatory elements. These findings define the aerobicity stimulon and establish a unifying framework for understanding bacterial respiratory flexibility, demonstrating how transcriptional networks and metabolic systems integrate to achieve energy homeostasis and bioenergetic resilience.

systems biology↗

bioRxiv2025

Evolution guided tolerance engineering of Pseudomonas putida KT2440 for production of the sustainable aviation fuel precursor isoprenol

Isoprenol (3-methyl-3-buten-1-ol) is a sustainable aviation fuel precursor and commodity chemical which can be microbially synthesized from renewable carbon streams. Its production has been demonstrated in Pseudomonas putida KT2440 but its titers, rates, and yields have yet to reach commercially viable levels, potentially due to its inherent toxicity. We hypothesized that utilization of Tolerization Adaptive Laboratory Evolution (TALE) would generate P. putida hosts more tolerant to isoprenol and suitable for enhanced production phenotypes. Here, we performed a comprehensive TALE campaign using three strains, the wild-type and two strains lacking subsets of known isoprenol catabolism and transport functions in quadruplicate independently evolved lineages. Several evolved clones from each starting strain displayed robust growth (up to 0.2 h-1) at 8 g/L of isoprenol, where starting strains could not grow. Whole genome resequencing of the 12 independent strain lineages identified convergent mutations. Reverse engineering four commonly mutated regions individually (gnuR, ttgB-PP_1394, PP_3024-PP_5558, PP_1695) each resulted in a partial recovery of the tolerance phenotypes observed in the evolved strains. Additionally, a proteomics-guided deletion of the master motility regulator, fleQ, in an evolved clone alleviated the tolerance vs. production trade-off, restoring isoprenol titers and consumption to levels observed in the starting strains. Collectively, this work demonstrated that an integrated strategy of laboratory evolution and rational engineering was effective to develop robust biofuel production hosts with minimized product toxicity.

microbiology↗

bioRxiv2025

A Diverse Genetic Basis for Metabolic Reactions is Revealed Through Pangenome analysis

Sequenced genomes for thousands of strains of a bacterial species allow for a comprehensive analysis of its pangenome. We present a pangenome study of Escherichia colis metabolism by formulating gene-to-protein-to-reaction associations (GPRs) for about 2,700 metabolic reactions in 2,377 fully sequenced strains. On one hand, these GPRs reconstruct strain-specific networks that allow computational predictions (and experimental validation) of metabolic phenotypes, while on the other hand, they give the genetic basis for a given metabolic reaction in every strain. A pangenome-wide analysis of GPRs shows that: 1) We can reveal the genetic basis for a specific metabolic property at the species level; 2) The genetic basis for many metabolic reactions is diverse; 3) Many rare genes show variation in the genes genomic neighborhood which often contain genes from transposable elements, 4) Many rare genes show large-scale fragmentation and horizontal gene transfer (>11,000 rare genes in 2,377 strains); and 5) The aromatic amino acids and branched chain amino acids pathways are enriched with rare genes, with Acetolactate synthase having 29 distinct genes. Thus, analysis of GPRs across the pangenome reveals a complex dynamic evolutionary history of metabolism, revealing the role of conserved, fragmented, and horizontally transferred metabolic genes.

systems biology↗

bioRxiv2024

Metabolic growth coupling strategies for in vivo enzyme selection systems

Whole-cell biocatalysis facilitates the production of a wide range of industrially and pharmaceutically relevant molecules from sustainable feedstocks such as plastic wastes, carbon dioxide, lignocellulose, or plant-based sugar sources. The identification and use of efficient enzymes in the applied biocatalyst is key to establishing economically feasible production processes. The generation and selection of favorable enzyme variants in adaptive laboratory evolution experiments using growth as a selection criterion is facilitated by tightly coupling enzyme catalytic activity to microbial metabolic activity. Here, we present a computational workflow to design strains that have a severe, growth-limiting metabolic chokepoint through a shared class of enzymes. The resulting chassis cell, termed enzyme selection system (ESS), is a platform for growth-coupling any enzyme from the respective enzyme class, thus offering cross-pathway application for enzyme engineering purposes. By applying the constraint-based modeling workflow, a publicly accessible database of 25,505 potential and experimentally tractable ESS designs was built for Escherichia coli and a broad range of production pathways with biotechnological relevance. Model-based analysis of the generated design database reveals a general design principle that the target enzyme activity is linked to overall microbial metabolic activity, not just the synthesis of one biomass precursor. Furthermore, the use of currently available genome-reduced strains or one preeminent carbon source does not significantly enable or improve growth-coupling of target enzymes. Most importantly, observed trade-offs between the predicted viability of ESSs, the design-inflicted metabolic perturbations, and the coupling strength suggest that a suboptimal coupling has benefits regarding the experimental implementation of ESSs and growth-coupling in general. Overall, the computed design database, which is accessible through https://biosustain.github.io/ESS-Designs/, and its analysis lay the foundation for generating valuable in vivo ESSs for a range of biotechnological applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/613188v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@15d5a10org.highwire.dtl.DTLVardef@1c4067aorg.highwire.dtl.DTLVardef@856ce9org.highwire.dtl.DTLVardef@1b14cdb_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG HighlightsO_LIEnzyme selection system designs link enzyme activities to global metabolic processes. C_LIO_LIEnzymes can be categorized based on growth-couplable reaction stoichiometries. C_LIO_LIA database of strain designs for building enzyme selection systems was created. C_LIO_LIEnzyme selection systems enable optimization of a range product synthesis pathways. C_LIO_LIApplication recommendations: weakly coupled enzyme activities can have practical advantages. C_LI

systems biology↗

bioRxiv2024

Multi-scale reactor designs extend the physical limits of CO2 fixation

CO2 valorization is a promising strategy for climate adaptation and transitioning towards a circular carbon economy. Here, we present a multi-scale, integrated systems approach for designing biomanufacturing systems that can utilize CO2 as a feedstock, focusing on the Wood-Ljungdahl and reductive glycine pathways. This approach relies on first principles, coupling the optimization of pathway and process variables. We examine the CO2-fixation capacity of both pathways in single- and multi-compartment reactor systems, demonstrating that the reductive glycine pathway has the potential to fix CO2 at significantly higher rates than photosynthetic organisms. We show that small differences in the energy-dissipative and stoichiometric structures of carbon-fixation pathways could significantly impact optimal designs and feasible design spaces. Our first-principle, systems-level approach quantifies these differences and uncovers strategies to expand the design space and extend the physical limits of carbon fixation, offering insights into pathway selection and process configurations for efficient biomanufacturing.

bioengineering↗

bioRxiv2024

PanKB: An interactive microbial pangenome knowledgebase for research, biotechnological innovation, and knowledge mining

The exponential growth of microbial genome data presents unprecedented opportunities for mining the potential of microorganisms. The burgeoning field of pangenomics offers a framework for extracting insights from this big biological data. Recent advances in microbial pangenomic research have generated substantial data and literature, yielding valuable knowledge across diverse microbial species. PanKB (pankb.org), a knowledgebase designed for microbial pangenomics research and biotechnological applications, was built to capitalize on this wealth of information. PanKB currently includes 51 pangenomes on 8 industrially relevant microbial families, comprising 8, 402 genomes, over 500, 000 genes, and over 7M mutations. To describe this data, PanKB implements four main components: 1) Interactive pangenomic analytics to facilitate exploration, intuition, and potential discoveries; 2) Alleleomic analytics, a pangenomic- scale analysis of variants, providing insights into intra-species sequence variation and potential mutations for applications; 3) A global search function enabling broad and deep investigations across pangenomes to power research and bioengineering workflows; 4) A bibliome of 833 open- access pangenomic papers and an interface with an LLM that can answer in-depth questions using their knowledge. PanKB empowers researchers and bioengineers to harness the full potential of microbial pangenomics and serves as a valuable resource bridging the gap between pangenomic data and practical applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/608241v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@4d3daaorg.highwire.dtl.DTLVardef@10b6d49org.highwire.dtl.DTLVardef@133da4forg.highwire.dtl.DTLVardef@141ae7e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

The Pangenome of Escherichia coli

Thousands of complete genome sequences for strains of a species that are now available enable the advancement of pangenome analytics to a new level of sophistication. We collected 2,377 publicly-available complete genomes of Escherichia coli for detailed pangenome analysis. The core genome and accessory genomes consisted of 2,398 and 5,182 genes, respectively. We developed a machine learning approach to define the accessory genes characterizing the major phylogroups of E. coli plus Shigella: A, B1, B2, C, D, E, F, G, and Shigella. The analysis resulted in a detailed structure of the genetic basis of the phylogroups differential traits. This pangenome structure was largely consistent with a housekeeping-gene-based MLST distribution, sequence-based Mash distance, and the Clermont quadruplex classification. The rare genome consisted of 163,619 genes, about 79% of which represented variations of 315 underlying transposon elements. This analysis generated a mathematical definition of the genetic basis for a species.

genomics↗

bioRxiv2024

Extracellular Respiration is a Latent Energy Metabolism in Escherichia coli

Diverse microbial species utilize redox shuttles to exchange electrons with their environment through mediated extracellular electron transfer (EET). This process maintains redox homeostasis and supports anaerobic survival across diverse microbial communities. Although mediated EET has been extensively leveraged for bioelectrocatalysis and bioelectronics for decades, fundamental questions remain about how these redox shuttles are reduced within cells and their bioenergetic implications. This knowledge gap limits our understanding of the physiological roles of mediated EET in various microbes and hampers the development of efficient microbial electrochemical technologies. To address this, we developed a methodology integrating genome editing, electrochemistry, and systems biology to investigate the mechanism and bioenergetic implications of mediated EET in bacteria. Using this approach, we uncovered a mediated EET mechanism in Escherichia coli. In the absence of alternative electron sinks, the redox cycling of 2-hydroxy-1,4-naphthoquinone (HNQ) via a cytoplasmic nitroreductase enabled E. coli to respire and grow on an extracellular electrode. Genome-scale metabolic modeling suggested that HNQ- mediated EET offers a more energetically favorable route for supporting anaerobic growth than canonical fermentation. Transcriptome analysis revealed redox perturbations in response to HNQ and identified rapid metabolic adaptations that support growth. This work demonstrates that E. coli can grow independently of classical electron transport chains and fermentative pathways, unveiling a new type of anaerobic energy metabolism.

systems biology↗

bioRxiv2024

Establishing comprehensive quaternary structural proteomes from genome sequence

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organisms genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions. SignificanceAdvancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a users query, maps the 3D location of actionable datatypes (e.g., active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

bioinformatics↗

bioRxiv2024

Pangenome mining of the Streptomyces genus redefines their biosynthetic potential

BackgroundStreptomyces is a highly diverse genus known for the production of secondary or specialized metabolites with a wide range of applications in the medical and agricultural industries. Several thousand complete or nearly-complete Streptomyces genome sequences are now available, affording the opportunity to deeply investigate the biosynthetic potential within these organisms and to advance natural product discovery initiatives. ResultWe performed pangenome analysis on 2,371 Streptomyces genomes, including approximately 1,200 complete assemblies. Employing a data-driven approach based on genome similarities, the Streptomyces genus was classified into 7 primary and 42 secondary MASH-clusters, forming the basis for a comprehensive pangenome mining. A refined workflow for grouping biosynthetic gene clusters (BGCs) redefined their diversity across different MASH-clusters. This workflow also reassigned 2,729 known BGC families to only 440 families, a reduction caused by inaccuracies in BGC boundary detections. When the genomic location of BGCs is included in the analysis, a conserved genomic structure (synteny) among BGCs becomes apparent within species and MASH-clusters. This synteny suggests that vertical inheritance is a major factor in the acquisition of new BGCs. ConclusionOur analysis of a genomic dataset at a scale of thousands of genomes refined predictions of BGC diversity using MASH-clusters as a basis for pangenome analysis. The observed conservation in the order of BGCs genomic locations showed that the BGCs are vertically inherited. The presented workflow and the in-depth analysis pave the way for large-scale pangenome investigations and enhance our understanding of the biosynthetic potential of the Streptomyces genus.

systems biology↗

bioRxiv2024

Trade-off Between Resistance and Persistence in High Cell Density Escherichia Coli Cultures

Microbes experience high cell density in many environments that come with diverse resource limitations and stresses. However, high density physiology remains poorly understood. We utilized well-controlled culturing systems to grow wild-type and metabolically engineered Escherichia coli strains into high cell densities (50-80 g Cdry cell weight L-1) and determine the associated transcriptional dynamics. Knowledge-enriched machine-learning-based analytics reveal distinct stress-related gene expression patterns that are consistent with a fundamental trade-off between resistance and persistence. We suggest that this trade-off explains observed growth arrests in high-density cultures and that it results from the disruption of cellular homeostasis, due to reallocation of limited cellular resources from resistance functions towards maintenance requirements of engineered production pathways. This study deepens our understanding of high-density physiology and demonstrates its importance to fundamental biomanufacturing challenges.

microbiology↗

bioRxiv2024

A treasure trove of 1,034 actinomycete genomes

Filamentous Actinobacteria, recently renamed Actinomycetia, are the most prolific source of microbial bioactive natural products. Studies on biosynthetic gene clusters benefit from or require chromosome-level assemblies. Here, we provide DNA sequences from more than 1,000 isolates: 881 complete genomes and 153 near-complete genomes, representing 28 genera and 389 species, including 244 likely novel species. All genomes are from filamentous isolates of the class Actinomycetia from the NBC culture collection. The largest genus is Streptomyces with 886 genomes including 742 complete assemblies. We use this data to show that analysis of complete genomes can bring biological understanding not previously derived from more fragmented sequences or less systematic datasets. We document the central and structured location of core genes and distal location of specialized metabolite biosynthetic gene clusters and duplicate core genes on the linear Streptomyces chromosome, and analyze the content and length of the terminal inverted repeats which are characteristic for Streptomyces. We then analyze the diversity of trans-AT polyketide synthase biosynthetic gene clusters, which encodes the machinery of a biotechnologically highly interesting compound class. These insights have both ecological and biotechnological implications in understanding the importance of high quality genomic resources and the complex role synteny plays in Actinomycetia biology.

microbiology↗