Biology subjects

Sintsova, A.

Publications and source records attributed to Sintsova, A..

18 recordsLinked to original sources

bioRxiv2026

Genome-scale metabolic models for a synthetic soil microbial community as a path for understanding community functioning

Microbial communities drive essential ecosystem processes, yet community-level behavior often deviates from predictions based on single-species studies. This mismatch reflects the context-dependent nature of nutrient dependencies, metabolic interactions, and resource availability in complex environments. Here, we present a mechanistic, species-resolved framework to dissect metabolism and nutrient exchange in a defined 21-member soil synthetic community spanning five bacterial phyla. For each isolate, we reconstructed and manually curated thermodynamically constrained genome-scale metabolic models, reconciling predictions with growth phenotypes across rich and minimal media. We mapped minimal nutrient requirements, cataloged environment-specific uptake and secretion profiles, and compared metabolic pathways to identify potential competitive and cooperative interactions. Using community-scale metabolomics, we assigned putative producers and consumers for detected metabolites and revealed medium-dependent shifts in niche overlap. This approach exposes metabolic strategies that govern community function and resilience, offering a predictive basis for understanding and manipulating microbiomes. Our findings highlight how species-level metabolic maps can clarify why microbial interventions succeed or fail and guide targeted manipulations in soil ecosystems.

systems biology↗

bioRxiv2026

The Ocean Microbiomics Database reveals thermal niches and projected pressure on marine microbes in a warming ocean

Temperature is a key driver of ocean microbial community structure, yet its role in shaping global distributions and their response to warming remains unclear due to fragmented studies, inconsistent methods, and limited environmental context. We present the Ocean Microbiomics Database (OMDB) containing 274,282 genomes forming 31,058 species-level clusters, searchable at https://omdb.microbiomics.io. We show surface temperature is predicted from community composition, driven by thermal niche partitioning among congeneric taxa. Using these thermal niches to model present-day distributions globally, we find that projected warming results in microbial richness declining faster than relative abundance, with losses concentrated at high latitudes and among poorly characterized lineages. Resolving 5,891 species into four thermal clusters reveals ecological structure correlated with genome streamlining, protein thermostability, and marker-gene physicochemistry, enabling prediction of a microorganism's abundance-maximizing temperature directly from its coding sequence. This positions OMDB as a platform spanning molecular traits to global ecology, offering a genome-resolved foundation for understanding how temperature, shown to be a primary driver of ocean microbial life, will continue to shape it as the ocean warms.

microbiology↗

bioRxiv2026

Nuclear stress bodies enable a germline-specific transcriptional stress response in Drosophila

The germline ensures the continuity of genetic information across generations, but how this immortal lineage functions under stress conditions remains incompletely understood. Here, we identify that heat shock factor (Hsf), a conserved master regulator of the stress response, drives the expression of transposable elements (TEs), in addition to molecular chaperones upon heat shock in Drosophila gonads. In germ cells, this potential intra-genomic conflict is countered by the formation of nuclear stress bodies (nSBs) at non-coding satellite DNA repeats. Using chemical and genetic perturbations, we demonstrate that nSBs are both necessary and sufficient to delay Hsf-dependent transcription. Notably, this nSB-mediated delay, in tandem with the piRNA pathway, allows germ cells to selectively express molecular chaperones, but not transposable elements, upon heat shock. Overall, we propose that this unique transcriptional stress response preserves germline function and evolutionary fitness, especially in natural populations routinely exposed to environmental stress.

cell biology↗

bioRxiv2026

Biphasic bacterial community assembly predicted from generalized first principles of monoculture growth and inferred species interactions

Microbial communities occur in all habitats, yet how individual growth on available nutrients scales to community assembly remains poorly understood. This gap stems largely from the unknown effects of species interactions. These interactions arise because individual populations both consume and transform primary substrates into metabolites exploitable by others, and because parasitic and predatory mechanisms can release cellular building blocks that enable nutrient reuse. Here, we present a mathematical framework that predicts community growth and compositional succession from monoculture growth kinetics, resource availability, and species interaction parameters. To parametrize species interactions, we use a simulated-annealing optimization algorithm to search parameter space for sets that minimize the difference between modeled community growth and experimental time series from soil microcosms inoculated with defined communities of 20 or 21 soil isolates, with or without an opportunistic bacteriovorous member. The optimized interaction parameter sets were then used to predict growth dynamics in an independent 21-member community and in species drop-out communities. We find that community development is biphasic: an initial phase dominated by competition for primary resources driven by inherent strain growth kinetics, followed by a phase governed by cross-feeding and biomass formation on released byproducts. Paired metatranscriptomic analysis corroborated predicted shifts in individual growth states and revealed metabolic repurposing associated with the sudden renewed availability of metabolites and cellular building blocks. Model simulations that excluded species interactions reproduced only one-fifth of the observed community biomass, highlighting the importance of cross-feeding for soil community growth. Overall, models that integrate monoculture growth kinetics with inferred species interactions can predict the dynamics of medium-complexity communities from starting inocula even when environmental nutrient composition is largely unknown.

microbiology↗

bioRxiv2026

Competition against the intestinal microbiota selects for pathoadaptive traits in ESBL E. coli

The intestinal tract is a reservoir for Extended-Spectrum {beta}-Lactamase (ESBL)-producing Escherichia coli. Asymptomatic gut colonization by these pathobionts represents a major risk for extraintestinal infections. Despite clinical relevance, the genetic basis of gut colonization by ESBL E. coli remains poorly understood. Here, we determined how the microbiota shapes the fitness landscape of diverse ESBL E. coli strains, defining the functional requirements for intestinal colonization. In microbiota-depleted hosts, colonization relies mostly on metabolic functions. In contrast, in mice harbouring a microbiota, pathoadaptive functions associated with adhesion and biofilm formation are dominant determinants of E. coli fitness, together with accessory virulence functions. Consistent with these observations, experimental evolution in mice reveals convergent adaptation of ESBL E. coli to the presence of a complex microbiota through enhanced adhesion. These findings establish the microbiota as a major ecological driver of pathoadaptation in antibiotic-resistant pathobionts.

microbiology↗

bioRxiv2026

Plasticity of genetic regulation during cellular learning

Even under physiological conditions, cells are exposed to multiple, spatially and temporally complex signals and need to regularly adjust their response to survive and function. At least in some cases, identifying the appropriate response relies on the ability cells to learn from experience. For example, budding yeast cells learn to ignore futile mating signals. Using this paradigm, we investigated the genetic requirements supporting learning in single cells. We show that it arises from the dynamics of a large, highly redundant and plastic genetic network, where the contribution of most genes to learning varies across experimental replicates. Furthermore, this network is highly resistant to genetic perturbations and involves a broad panel of cellular functions and sensing pathways, suggesting that it can integrate a large diversity of inputs. Together, our data support the notion that cellular learning is an emerging feature of the information storage capability inherent to large sets of interacting genes, indicating that it should be widely conserved across cell types.

cell biology↗

bioRxiv2026

Meiotic pairing through barcode-like satellite DNA repeats

During meiosis, chromosomes must find, pair, and synapse with their homologous partners in the crowded milieu of the nucleus1. Although homology detection is generally attributed to recombination, pairing and synapsis can occur in its absence2-10, suggesting alternate mechanisms that discriminate between homologous and non-homologous chromosomes. In many eukaryotes, tandem repeats known as satellite DNA facilitate inter-chromosomal associations11. Notably, their non-uniform distribution across chromosomes gives rise to homologue-specific satellite DNA barcodes12-14, which have been speculated to enable meiotic pairing15-18. However, satellite DNA function remains actively debated since these repeats cannot be manipulated in most model organisms. Here, we use satellite DNA deletion, duplication, and translocation strains that are unique to Drosophila to demonstrate that repeat mismatches perturb meiotic pairing, particularly at centromeres and pericentromeres. In the absence of satellite DNA homology, pairing is antagonized by the HORMAD protein, Mad2, while a Pachytene checkpoint 2 (Pch2)-dependent meiotic delay restores pairing. Remarkably, pairing defects are also observed in the progeny of D. melanogaster natural populations that have diverged in their satellite DNA content. Finally, compromised meiotic pairing is strongly correlated with mid-oogenesis cell death, a quality control mechanism that likely culls defective oocytes to prevent chromosome mis-segregation and aneuploidy. These findings resolve a long-standing debate on satellite DNA functionality by demonstrating a barcode-like role in homology detection. We propose that this repeat-based pairing mechanism exerts an underappreciated selective pressure, constraining the divergence of rapidly evolving satellite DNA within interbreeding natural populations.

genetics↗

bioRxiv2025

Transcriptomic profiles of single-copy marker genes enable predicting bacterial growth states in microbial communities

Studying microbial community dynamics is fundamental to better understand ecosystem stability, resilience and environmental change. Community composition changes with the growth of individual members, yet current methods to estimate microbial growth in communities face substantial limitations. For example, genome sequence-based estimates of maximum growth rates may not reflect growth patterns in the natural environment well, and metagenomic in situ growth prediction requires the availability of reference genomes and shows limited accuracy for slow-growing bacteria. Gene expression data provide an information-rich readout of community activity that could reflect growth, however, cross-species comparisons in community settings remain challenging. An approach using expression signatures of universal, single-copy marker genes provides independence from reference genomes and may thereby enable comparability across species. Here, we present a transcriptomic, marker gene-based growth classifier that predicts the growth states of bacterial strains from different phyla cultivated in diverse conditions. We demonstrate its application in vivo in gnotobiotic mice carrying the same bacterial strains, and in a more complex synthetic community, where predicted growth states align with reported growth inhibition induced by systemic inflammatory response. This approach offers a new method for predicting bacterial growth states across species, with potential for broad application in the study of microbial growth dynamics at the whole community level.

microbiology↗

bioRxiv2025

Nuclear mechanostability emerges from satellite DNA condensation into chromocenters

As the largest organelle, the nucleus endures significant mechanical stresses over the cellular lifespan, and mechanostability, i.e. the ability to resist deformation, is critical for genome integrity and function. Here, we reveal that nuclear mechanostability is an emergent property arising from the clustering of satellite DNA repeats into nuclear condensates known as chromocenters. Targeted chromocenter disruption in Drosophila testes subjected to natural and artificial mechanical stress compromises nuclear mechanostability, leading to deformed nuclei, DNA damage, and chromosome breaks. Conversely, enhancing chromocenter coalescence through genetic means improves mechanostability. Molecular dynamics simulations suggest that chromocenters enable physically linked chromosomes to respond collectively, rather than individually, to mechanical challenge, and dissipate external forces over a larger nuclear surface. We propose that the satellite DNA-dependent mechanostability framework described here likely extends to other cells and tissues facing mechanical stress, and offers an explanation for the evolutionary success of these non-coding repeats across eukaryotes.

cell biology↗

bioRxiv2024

Salmonella multimutants enable efficient identification of SPI-2 effector protein function in gut inflammation and systemic colonization

Salmonella enterica spp. rely on translocation of effector proteins through the SPI-2 encoded type III secretion system (T3SS) to achieve pathogenesis. More than 30 effectors contribute to manipulation of host cells through diverse mechanisms, but interdependency or redundancy between effectors complicates the discovery of effector phenotypes using single mutant strains. Here, we engineer six mutant strains to be deficient in cohorts of SPI-2 effector proteins, as defined by their reported function. Using various animal models of infection, we show that three principle phenotypes define the functional contribution of the SPI-2 T3SS to infection. Multimutant strains deficient for intracellular replication, for manipulation of host cell defences, or for expression of virulence plasmid effectors all showed strong attenuation in vivo, while mutants representing approximately half of the known effector complement showed phenotypes similar to the wild-type parent strain. By additionally removing the SPI-1 T3SS, we find cohorts of effector proteins that contribute to SPI-2 T3SS-driven enhancement of gut inflammation. Further, we provide an example of how iterative mutation can be used to find a minimal number of effector deletions required for attenuation, and thus establish that the SPI-2 effectors SopD2 and GtgE are critical for the promotion of gut inflammation and mucosal pathology. This strategy provides a powerful toolset for simultaneous parallel screening of all known SPI-2 effectors in a single experimental context, and further facilitates the identification of the responsible effectors, and thereby provides an efficient approach to study how individual effectors contribute to disease.

microbiology↗

bioRxiv2024

Monosaccharides Drive Salmonella Gut Colonization in a Context-Dependent Manner

The carbohydrates that fuel gut colonization by S. Typhimurium are not fully known. To investigate this, we designed a quality-controlled mutant pool to probe the metabolic capabilities of this enteric pathogen. Using WISH-barcoding, we tested 35 metabolic mutants across five different mouse models, allowing us to differentiate between context-dependent and context-independent nutrient sources. Results showed that S. Typhimurium uses D-glucose, D-mannose, D-fructose, and D-galactose as context-independent carbohydrates across all models. The utilization of N-acetylglucosamine and hexuronates, on the other hand, was context-dependent. Furthermore, we showed that D-fructose is important in strain-to-strain competition between Salmonella serovars. Complementary experiments confirmed that D-glucose, D-fructose, and D-galactose are excellent niches for S. Typhimurium to exploit during colonization. Quantitative measurements revealed sufficient amounts of D-glucose and D-galactose in the murine cecum to drive S. Typhimurium colonization. Understanding these key substrates and their context-dependent use by enteric pathogens will inform the future design of probiotics and therapeutics to prevent diarrheal infections such as non-typhoidal salmonellosis.

microbiology↗

bioRxiv2023

mBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants and isogenic strain populations

DNA barcoding has become a powerful tool for assessing the fitness of strains in a variety of studies, including random transposon mutagenesis screens, attenuation of site-directed mutants, and population dynamics of isogenic strain pools. However, the statistical analysis, visualization and contextualization of the data resulting from such experiments can be complex and require bioinformatic skills. Here, we developed mBARq, a user-friendly tool designed to simplify these steps for diverse experimental setups. The tool is seamlessly integrated with an intuitive web app for interactive data exploration via the STRING and KEGG databases to accelerate scientific discovery.

bioinformatics↗

bioRxiv2023

A nuclear architecture screen in Drosophila identifies Stonewall as a link between chromatin position at the nuclear periphery and germline stem cell fate

The association of genomic loci to the nuclear periphery is proposed to facilitate cell-type specific gene repression and influence cell fate decisions. However, the interplay between gene position and expression remains incompletely understood, in part because the proteins that position genomic loci at the nuclear periphery remain unidentified. Here, we used an Oligopaint-based HiDRO screen targeting [~]1000 genes to discover novel regulators of nuclear architecture in Drosophila cells. We identified the heterochromatin-associated protein, Stonewall (Stwl), as a factor promoting perinuclear chromatin positioning. In female germline stem cells (GSCs), Stwl binds and positions chromatin loci, including GSC differentiation genes, at the nuclear periphery. Strikingly, Stwl-dependent perinuclear positioning is associated with transcriptional repression, highlighting a likely mechanism for Stwls known role in GSC maintenance and ovary homeostasis. Thus, our study identifies perinuclear anchors in Drosophila and demonstrates the importance of gene repression at the nuclear periphery for cell fate.

cell biology↗

bioRxiv2021

Ferric Citrate Uptake is a Virulence Factor in Uropathogenic Escherichia coli

More than half of women will experience a urinary tract infection (UTI) with uropathogenic Escherichia coli (UPEC) causing [~]80% of uncomplicated cases. Iron acquisition systems are essential for uropathogenesis, and UPEC encode functionally redundant iron acquisition systems, underlining their importance. However, a recent UPEC clinical isolate, HM7 lacks this functional redundancy and instead encodes a sole siderophore, enterobactin. To determine if E. coli HM7 possesses unidentified iron acquisition systems, we performed RNA-sequencing under iron-limiting conditions and demonstrated that the ferric citrate uptake system (fecABCDE and fecIR) was highly upregulated. Importantly, there are high levels of citrate within urine, some of which is bound to iron, and the fec system is highly enriched in UPEC isolates compared to environmental or fecal strains. Therefore, we hypothesized that HM7 and other similar strains use the fec system to acquire iron in the host. Deletion of both enterobactin biosynthesis and ferric citrate uptake ({Delta}entB/{Delta}fecA) abrogates use of ferric citrate as an iron source and fecA provides an advantage in human urine in absence of enterobactin. However, in a UTI mouse model, fecA is a fitness factor independent of enterobactin production, likely due to the action of host Lipocalin-2 chelating ferrienterobactin. These findings indicate that ferric citrate uptake is used as an iron source when siderophore efficacy is limited, such as in the host during UTI. Defining these novel compensatory mechanisms and understanding the nutritional hierarchy of preferred iron sources within the urinary tract are important in the search for new approaches to combat UTI. ImportanceUPEC, the primary causative agent of uncomplicated UTI is responsible for five billion dollars in healthcare costs in the US each year. Rates of antibiotic resistance are on the rise therefore it is vital to understand the mechanisms of UPEC pathogenesis to uncover potential targets for novel therapeutics. Iron acquisition systems used to obtain iron from sequestered host sources are essential for UPEC survival during UTI and have been used as vaccine targets to prevent infection. This study reveals the ferric citrate uptake system is another important iron acquisition system that is highly enriched in UPEC strains. Ferric citrate uptake has not previously been associated with these pathogenic isolates, underlining the importance of the continued study of these strains to fully understand their mechanisms of pathogenesis.

microbiology↗

bioRxiv2020

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens

Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable conversion of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have vast potential as genome editing tools for basic research and gene therapy, their application has been hampered by a broad variation in editing efficiencies on different genomic loci. Here we perform an extensive analysis of adenine- and cytosine base editors on thousands of lentivirally integrated genetic sequences and establish BE-DICT, an attention-based deep learning algorithm capable of predicting base editing outcomes with high accuracy. BE-DICT is a versatile tool that in principle can be trained on any novel base editor variant, facilitating the application of base editing for research and therapy.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2020

Optimization of an Experimental Vaccine to Prevent Escherichia coli Urinary Tract Infection

Urinary tract infections (UTI) affect half of all women at least once during their lifetime. The rise in extended-spectrum beta-lactamase-producing strains and potential for carbapenem resistance within uropathogenic Escherichia coli (UPEC), the most common causative agent of UTIs, creates an urgent need for vaccine development. Intranasal immunization of mice with UPEC outer membrane iron receptors, FyuA, Hma, IreA, or IutA, conjugated to cholera toxin, provides protection in the bladder or kidneys when challenged with UPEC CFT073 or 536. Based on these data, we sought to optimize the vaccination route (intramuscular, intranasal, or subcutaneous) in combination with adjuvants suitable for human use including alum, monophosphoryl lipid A (MPLA), unmethylated CpG synthetic oligodeoxynucleotides (CpG), polyinosinic:polycytodylic acid (polyIC), and mutated heat-labile E. coli enterotoxin (dmLT). Mice intranasally vaccinated with dmLT-IutA or dmLT-Hma displayed a significant reduction in bladder colonization (86-fold and 32-fold, respectively) with 40-42% of mice having no detectable colony forming units (CFU). Intranasal vaccination of mice with CpG-IutA and polyIC-IutA significantly reduced kidney colonization (131-fold) and urine CFU (22-fold), respectively. dmLT generated the most consistently robust antibody response in intranasally immunized mice, while MPLA and alum produced greater concentrations of antigen-specific serum IgG with intramuscular immunization. Based on these results, we conclude that intranasal administration of Hma or IutA formulated with dmLT adjuvant provides the greatest protection from UPEC UTI. This study advances our progress toward a vaccine against uncomplicated UTI, which will significantly improve the quality of life for women burdened by recurrent UTI and enable better antibiotic stewardship. ImportanceUrinary tract infections (UTI) are among the most common bacterial infection in humans, affecting half of all women at least once during their lifetimes. The rise in antibiotic resistance and health care costs emphasizes the need to develop a vaccine against the most common UTI pathogen, Escherichia coli. Vaccinating mice intranasally with a detoxified heat-labile enterotoxin and two surface exposed receptors, Hma or IutA, significantly reduced bacterial burden in the bladder. This work highlights progress in the development of a UTI vaccine formulated with adjuvants suitable for human use and antigens that encode outer membrane iron receptors required for infection in the iron-limited urinary tract.

microbiology↗

bioRxiv2020

The Gene Expression Profile of Uropathogenic Escherichia coli in Women with Uncomplicated Urinary Tract Infections Is Recapitulated in the Mouse Model

Uropathogenic Escherichia coli (UPEC) is the primary causative agent of uncomplicated urinary tract infections (UTIs). UPEC fitness and virulence determinants have been evaluated in a variety of laboratory settings that include a well-established mouse model of UTI. However, the extent to which bacterial physiology differs between experimental models and human infections remains largely understudied. To address this important question, we compared the transcriptomes of three different UPEC isolates in human infection and a variety of laboratory conditions including LB culture, filter-sterilized urine culture, and the UTI mouse model. We observed high correlation in gene expression between the mouse model and human infection in all three strains examined (Pearson correlation coefficient of 0.86-0.87). Only 175 of 3,266 (5.4%) genes shared by all three strains had significantly different expression levels, with the majority of them (145 genes) down-regulated in patients. Importantly, gene expression of both canonical virulence factors and metabolic machinery were highly similar between the mouse model and human infection, while the in vitro conditions displayed more substantial differences. Interestingly, comparison of gene expression between the mouse model and human infection hint at differences in bladder oxygenation as well as nutrient composition. In summary, our work strongly validates the continued use of this mouse model for the study of the pathogenesis of human UTI. ImportanceDifferent experimental models have been used to study UPEC pathogenesis including in vitro cultures in different media, tissue culture, as well as mouse models of infection. The latter is especially important since it allows evaluation of mechanisms of pathogenesis and potential therapeutic strategies against UPEC. Bacterial physiology is greatly shaped by environment and it is therefore critical to understand how closely bacterial physiology in any experimental model relates to human infection. In this study, we found a very strong correlation in bacterial gene expression between the mouse model and human UTI using identical strains, suggesting that the mouse model accurately mimics human infection, definitively supporting its continued use in UTI research.

microbiology↗

bioRxiv2019

Genetically diverse uropathogenic Escherichia coli adopt a common transcriptional program in patients with urinary tract infections

Uropathogenic Escherichia coli (UPEC) is the major causative agent of uncomplicated urinary tract infections (UTIs). A common virulence genotype of UPEC strains responsible for UTIs is yet to be defined, due to the large variation of virulence factors observed in UPEC strains. We hypothesized that studying UPEC functional responses in patients might reveal universal UPEC features that enable pathogenesis. Here we identify a transcriptional program shared by genetically diverse UPEC strains isolated from 14 patients during uncomplicated UTIs. Strikingly, this in vivo gene expression program is marked by upregulation of translational machinery, providing a mechanism for the rapid growth within the host. Our analysis indicates that switching to a more specialized catabolism and scavenging lifestyle in the host allows for the increased translational output. Our study identifies a common transcriptional program underlying UTIs and illuminates the molecular underpinnings that likely facilitate the fast growth rate of UPEC in infected patients.

microbiology↗