Biology subjects

Todor, H.

Publications and source records attributed to Todor, H..

10 recordsLinked to original sources

bioRxiv2026

Predicting the protein interaction landscape of a mycobacterial pathogen

High-dimensional phenotypic screens of bacterial loss-of-function mutant libraries have determined gene-gene connections and specific phenotypes for thousands of bacterial genes in many species, but deciphering the underlying mechanisms remains decidedly low-throughput. Here, we demonstrate the utility of proteome-wide AI-based protein-protein interaction (PPI) predictions for overcoming this gap by using pooled-AlphaFold3 to assess all [~]1.3 million possible pairwise interactions in the proteome of Mycobacterium leprae. We identify [~]2,000 strong and intermediate PPIs that underlie a significant fraction of phenotypes and gene-gene connections observed in large-scale chemical genomics screens from Mycobacterium tuberculosis, Mycobacterium smegmatis, and Corynebacterium glutamicum. This combined approach predicts specific functions for dozens of previously uncharacterized core, conserved, and essential mycobacterial proteins. We highlight new information derived from the study, including insights into mycobacterial envelope assembly, peptidoglycan remodeling, and new modulators of the central dogma enzymes RNA polymerase and DNA gyrase. These data establish combined pooled-AlphaFold3 PPI prediction and high-throughput genomics approach as the gold standard for large-scale characterization of protein function.

systems biology↗

bioRxiv2026

The phenotypic landscape of the model firmicute Bacillus subtilis

Firmicutes are gram-positive bacteria with important roles in human health, disease, and industry. However, more than a quarter of genes in the model firmicute Bacillus subtilis remain completely uncharacterized, including numerous core phylum-specific genes. Here, we design a compact pooled CRISPRi library targeting all protein-coding genes in B. subtilis and test its growth in [~]150 stress conditions. Using data from this screen as a hypothesis generator, we perform targeted experiments, revealing that the conserved essential firmicute protein YneF is part of the SRP co-translational protein secretion pathway. We also demonstrate that ECF-transporters play a previously unknown but broadly conserved role in cell wall homeostasis, perform an unbiased analysis of amino acid crossfeeding, and make additional discoveries about bacterial competition. In addition to these major contributions to our understanding of B. subtilis biology (and gram-positive firmicutes in general), this work provides a rich dataset that will nucleate future studies of uncharacterized genes and presents a framework for accessible full-genome functional genomic screens in other bacteria. SIGNIFICANCELarge-scale chemical genomics screens facilitate the characterization of genes by generating phenotypic data across a library of gene mutants. Here, using CRISPRi, we designed a compact pooled library targeting all genes in B. subtilis and screened growth of the library in [~]150 conditions. Importantly, we used this dataset to expand B. subtilis biology on levels ranging from molecular pathways to bacterial communities. We discovered a role for an essential firmicute gene in protein secretion, implicated two new players in cell wall homeostasis, and unraveled fundamental factors driving competition and cooperation in the soil. This rich dataset will serve as a hypothesis generator, expanding our set of bacterial phenotypic data and driving future experiments in B. subtilis and other gram-positive firmicutes.

microbiology↗

bioRxiv2025

The phenotypic landscape of the mycobacterial cell

The Mycobacteriales are an order of diverse bacteria that thrive in many environmental and host-associated niches. Because the most notorious member of this clade, Mycobacterium tuberculosis, is a major human pathogen, research on Mycobacteriales has focused on pathogenesis, and, as a consequence, many fundamental aspects of Mycobacterial biology remain understudied. Here, we address this gap by performing a genome-wide CRISPRi chemical genomics screen using a diverse set of >35 antibiotics, detergents, and other anti-microbials predominantly targeting the cell envelope of Mycobacterium smegmatis, a saprophytic model Mycobacterium. We highlight new information derived from this screen, including the identification of novel functions for previously uncharacterized conserved and essential genes (in mycolic acid and arabinogalactan synthesis), the discovery of a new drug scaffold/protein target pair, and insights into the mechanism of action of two commonly used antibiotics. These data are also a valuable resource for the mycobacterial research community, as they provide thousands of novel phenotypes for uncharacterized genes and meaningful phenotypic correlations between annotated and uncharacterized genes.

microbiology↗

bioRxiv2025

Predicting the protein interaction landscape of a free-living bacterium with pooled-AlphaFold3

Accurate prediction of protein complex structures by AlphaFold3 and similar programs has been used to predict the presence of protein-protein interactions (PPIs), but this technique has never been applied to an entire genome due to onerous computational requirements and questionable utility. Here we present pooled-PPI prediction, a technique that dramatically improves the accuracy of genome-scale screens compared to a paired approach while simultaneously reducing inference time ([~]2-fold) and the number of jobs ([~]100-fold). We use this technique to predict the structure of all 113,050 pairwise PPIs in Mycoplasma genitalium using only 2,027 AlphaFold3 jobs. This unbiased and comprehensive dataset was highly predictive of known interactions, revealed a previously unappreciated but widespread size bias in AlphaFold interface scores, correctly identified protein-protein interfaces in macromolecular complexes, and uncovered new biology in M. genitalium. This work establishes pooled-PPI prediction as a highly scalable method for uncovering protein-protein interactions and a powerful addition to the functional genomics toolkit.

systems biology↗

bioRxiv2024

Comprehensive double-mutant analysis of the Bacillus subtilis envelope using double-CRISPRi

Understanding bacterial gene function remains a major biological challenge. Double-mutant genetic interaction (GI) analysis addresses this challenge by uncovering the functional partners of targeted genes, allowing us to associate genes of unknown function with novel pathways and unravel connections between well-studied pathways, but is difficult to implement at the genome-scale. Here, we develop and use double-CRISPRi to systematically quantify genetic interactions at scale in the Bacillus subtilis envelope, including essential genes. We discover > 1000 known and novel genetic interactions. Our analysis pipeline and experimental follow-ups reveal the distinct roles of paralogous genes such as the mreB and mbl actin homologs, and identify new genes involved in the well-studied process of cell division. Overall, our study provides valuable insights into gene function and demonstrates the utility of double-CRISPRi for high-throughput dissection of bacterial gene networks, providing a blueprint for future studies in diverse bacterial species.

genomics↗

bioRxiv2024

Dual CRISPRi-Seq for genome-wide genetic interaction studies identifies key genes involved in the pneumococcal cell cycle

A major goal in biology is to uncover the relationship between genotype and phenotype. However, identifying gene function is often hampered by genetic redundancy. For example, under standard laboratory conditions, three-quarters of the genes in the human pathogen Streptococcus pneumoniae are non-essential. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. To uncover genetic interactions (GIs) in S. pneumoniae on a genome-wide scale, a generally applicable dual CRISPRi-Seq method and associated analysis pipeline was developed. Specifically, we created a library of 869 dual sgRNAs targeting high-confidence operons that encode essential and non-essential genes, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified, including 1,935 negative and 2,091 positive interactions. Besides known GIs, we found and confirmed previously unknown interactions involving genes responsible for fundamental cellular processes such as cell division, cell shape maintenance, and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. Lastly, all interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN) at https://veeninglab.shinyapps.io/PneumoGIN, which can serve as a starting point for new biological discoveries and translational research.

microbiology↗

bioRxiv2023

Lipopolysaccharide integrity primes bacterial sensitivity to a cell wall-degrading intermicrobial toxin

Gram-negative bacteria can antagonize neighboring microbes using a type VI secretion system (T6SS) to deliver toxins that target different essential cellular features. Despite the conserved nature of these targets, T6SS potency can vary across recipient species. To understand the molecular basis of intrinsic T6SS susceptibility, we screened for essential Escherichia coli genes that affect its survival when antagonized by a cell wall-degrading T6SS toxin from Pseudomonas aeruginosa, Tae1. We revealed genes associated with both the cell wall and a separate layer of the cell envelope, surface lipopolysaccharide, that modulate Tae1 toxicity in vivo. Disruption of lipopolysaccharide synthesis provided Escherichia coli (Eco) with novel resistance to Tae1, despite significant cell wall degradation. These data suggest that Tae1 toxicity is determined not only by direct substrate damage, but also by indirect cell envelope homeostasis activities. We also found that Tae1-resistant Eco exhibited reduced cell wall synthesis and overall slowed growth, suggesting that reactive cell envelope maintenance pathways could promote, not prevent, self-lysis. Together, our study highlights the consequences of co-regulating essential pathways on recipient fitness during interbacterial competition, and how antibacterial toxins leverage cellular vulnerabilities that are both direct and indirect to their specific targets in vivo.

microbiology↗

bioRxiv2023

Three bacterial DedA subfamilies with distinct functions and phylogenetic distribution

Recent studies in bacteria suggested that the broadly conserved but enigmatic DedA proteins function as undecaprenyl-phosphate (UndP) flippases, recycling this essential lipid carrier. To determine whether all DedA proteins have UndP flippase activity, we performed a phylogenetic analysis and correlated it to previously published experimental results and predicted structures. We uncovered three major DedA subfamilies: one contains UndP flippases, the second contains putative phospholipid flippases and is associated with aerobic metabolism, and the third is found only in specific Gram-negative phyla. IMPORTANCEDedA-family proteins are highly conserved and nearly ubiquitous integral membrane proteins found in Archaea, Bacteria, and Eukaryotes. Recent work revealed that eukaryotic DedA proteins are phospholipid scramblases and some bacterial DedA proteins are undecaprenyl phosphate flippases. We perform a phylogenetic analysis of this protein family in Bacteria revealing 3 DedA subfamilies with distinct phylogenetic distributions, genomic contexts, and putative functions. Our analysis lays the groundwork for a deeper understanding of DedA proteins and their role in maintaining and modifying the membrane.

molecular biology↗

bioRxiv2020

Rewiring the specificity of extra-cytoplasmic function sigma factors

SUMMARYBacterial genomes are being sequenced at an exponentially increasing rate, but our inability to decipher their transcriptional wiring limits our ability to derive new biology from these sequences. De novo determination of regulatory interactions requires accurate prediction of regulators’ DNA binding and precise determination of biologically significant binding sites. Here, we address these challenges by solving the DNA-specificity code of extra-cytoplasmic function sigma factors (ECF σs), a major family of bacterial regulators, and determining their regulons. We generated an aligned collection of ECF σs and their promoters by leveraging the auto-regulatory nature of ECF σs as a means of promoter discovery and analyzed it to identify and characterize the conserved amino acid – nucleotide interactions that determine promoter specificity. This enabled de novo prediction of ECF σ specificity, which we combined with a statistically rigorous phylogenetic foot-printing pipeline based on precomputed orthologs to predict the direct targets of ∼67% of ECF σs. This global survey indicated that ECF σs play varied roles: some are global regulators controlling many genes throughout the genome that are important under many conditions, while others are local regulators, controlling few closely linked genes in response to specific stimuli. This analysis reveals important organizing principles of bacterial gene regulation and presents a conceptual and computational framework for deciphering gene regulatory networks.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2019

Modulated efficacy CRISPRi reveals evolutionary conservation of essential gene expression-fitness relationships in bacteria

Essential genes are the central hubs of cellular networks. Despite their importance, the lack of high-throughput methods for titrating their expression has limited our understanding of the fitness landscapes against which essential gene expression levels are optimized. We developed a modified CRISPRi system leveraging the predictable reduction in efficacy of imperfectly matched sgRNAs to generate specific levels of CRISPRi activity and demonstrate its broad applicability in bacteria. Using libraries of mismatched sgRNAs, we characterized the expression-fitness relationships of essential genes in Escherichia coli and Bacillus subtilis. Remarkably, these relationships co-vary by pathway and are predominantly conserved between E. coli and B. subtilis despite ~ 2 billion years of evolutionary separation, suggesting that deeply conserved tradeoffs underlie bacterial homeostasis.\n\nOne Sentence SummaryBacterial essential genes have varying responses to CRISPRi knockdown that are largely conserved across ~2 billion years of evolution.

systems biology↗