Biology subjects

Lopez, P.

Publications and source records attributed to Lopez, P..

At least 19 recordsLinked to original sources

bioRxiv2026

GenDiMug: a generic inclusive multigraph framework to analyze genomic organizations and -omics data at multiple scales

After decades of investigation, analyses of genome organization remain challenging. This is because genome descriptions are very information-rich and usually rendered as a linear map of genomic features corresponding to an ordered list of position intervals on a nucleic acid macromolecular backbone. This formalism, while accurate, is not fully optimized to mathematically analyze all genome structural properties, in particular the relations between genomic features, nor to integrate large amounts of -omics data, such as transcriptomes, epigenomes, proteomes, meltomes or chromatin accessibility data, which are increasingly available. We therefore developed GenDiMug, a tool that uses a network representation of the genome as a backbone, providing a natural framework to integrate spatial and ontogenetic relationships between genomic features and multi-omics data. We illustrate how this generic approach can be applied to all sorts of genomes, both to visualize genomic topology at contig and chromosomal scales at base-pair resolution, and to analyze genome positional effects using various graph metrics. Using GenDiMug, we further reveal clumping of genes with similar expression levels in eukaryotic genomes and their possible circadian regulation in a photosynthetic alga.

bioinformatics↗

bioRxiv2026

Morphologic intratumoral heterogeneity from routine whole-slide histopathology is prognostic for survival in primary central nervous system lymphoma: development in the LOC Network and international external validation

Background: Clinical scores incompletely capture outcomes in primary central nervous system lymphoma (PCNSL). We quantified morphologic heterogeneity in pretreatment hematoxylin and eosin (H\&E) whole slides. Patients and methods: Three independent cohorts of immunocompetent, HIV- and EBV-negative patients treated recently were analyzed: LOC 2023 (122 slides), phase III BLOCAGE-01 (245 slides; NCT02313389), and external Barcelona (BCN; 41 slides). UNI embeddings, prototype learning, spatial metrics, and elastic-net Cox regression defined ITH-C. Results: Models achieved bootstrap-corrected concordance of 0.797--0.834. Age-, sex-, and KPS-adjusted ITH-C HRs were 1.29 (95\% CI 1.01--1.64), 1.27 (1.07--1.51), and 2.13 (1.35--3.37), respectively. Adding ITH-C increased MSKCC C-index from 0.671 to 0.717, 0.560 to 0.593, and 0.588 to 0.706. Spatial transcriptomics linked ITH-C to immune programs. Conclusions: Routine H\&E encodes prognostic spatial heterogeneity in PCNSL. ITH-C complements clinical scores, supporting prospective risk stratification.

bioinformatics↗

bioRxiv2026

Cardiolipin increases the peak of reversible traveling H+ fronts at the membrane surface

Cardiolipin (CL) is a phospholipid found in the inner mitochondrial membrane (IMM) where it increases the efficiency of ATP regeneration. We have investigated the hypothesis that this increase may result in part from CL concentrating H+ at the IMM surface through electrostatic interactions as the CL polar head is a dianion at physiological pH. To this aim, we compared the concentrations and movements of H+ at the surface of giant planar phosphatidylcholine (PC) membranes and 20% CL enriched PC membranes by recording their surface pH with the membrane-grafted pH probe fluorescein DHPE. CL enrichment of the membranes increased their surface H+ activity by a ~4 factor. Moreover, we observed non-gaussian spatial H+ concentration profiles with distance from a point H+ source with both PC and CL membranes suggesting that both lipids also induce interactions between probe molecules. A whole bath pH variation revealed that these interactions allow the traveling of reversible acidification fronts with constant speed over the membrane between high and low pH states. A reaction-diffusion model of these observations suggests that membranes support these fronts through a mechanism of autocatalytic (de)protonation of the membrane surface. In mitochondria, these fronts would result in transitions between high and low pH states, the low one having a larger H+ concentration in CL-enriched regions of the IMM. Such an increase at the inner leaflet of the IMM may increase efficiency of the respiratory chain whereas the increase at the outer leaflet may boost the ATP synthase rate.

biophysics↗

bioRxiv2025

Engineering Inducible Cell Fate Transitions by Harnessing Epigenetic Silencing

During development, cell-cell communication induces state transitions that are maintained by epigenetic regulation. Here, we harness endogenous epigenetic silencing machinery to engineer synthetic circuits that induce stable gene expression changes. Using synthetic Notch receptors that control the chromatin regulators KRAB and Dnmt3L, we developed input-sensing switches that induce self-sustained silencing of target loci. We used these modules to construct circuits in which combinatorial inputs direct a choice among multiple alternative states. These epigenetic switches can also be inverted to yield sustained activation of target genes. We demonstrate that these epigenetic switches can be used to drive morphological changes triggered by transient cell-cell interactions, but that remain stable over many cell divisions, as is observed in development. Additionally, these circuits can be used to drive the reprogramming of fibroblasts to a neuron-like state. These synthetic epigenetic circuits represent an important step towards engineering cell populations capable of coordinated multi-cell state decisions.

synthetic biology↗

bioRxiv2025

Antigen stimulation drives clonal expansion of latent CD4+ T cells using a full-length HIV latency reporter

HIV persistence despite years of ART suppression poses a major barrier to cure. Using a full-length latency reporter to generate HIV-infected, transcriptionally silent CD4+ T cells in vitro, we show that cognate DC:T cell interactions drive clonal expansion of latent T cells in an antigen dependent manner and that a pro-survival state within proliferating cells is reinforced through IL-7 signaling. Interestingly, we describe a dominant role for CD28 co-stimulation in regulating robust latent T cell proliferation which was partially reversed by PD-1 blockade. Our studies show that a gradual reduction in antigenic stimulation was sufficient to induce proliferative responses without measurable proviral reactivation. Thus, the magnitude of TCR/co-stimulatory signals during cognate APC:T cell interactions are key regulators of the underlying proliferative and survival programs maintaining the latent reservoir under ART suppression. Significance StatementViral replication can be effectively suppressed by antiretroviral therapy (ART) but is not curative due to persistence of latent virus in a stable reservoir in resting CD4+ T cells. We show that antigen recognition through cell-cell interactions is an important driver of latent T cell proliferation, and that modulating TCR stimulatory signaling independently regulates proliferative, survival and proviral reactivation potential in infected T cells. Our observations show that latent T cells retain their ability to engage other immune cells to support their long-term survival under ART suppression, similar to uninfected T cells. These characteristics of latent T cell pools represent an additional hurdle to eradicating the reservoir.

immunology↗

bioRxiv2025

Robust Serum Proteomic Signatures of APOE2

We previously identified a signature of 16 serum proteins that highlighted a role of the e2 allele of APOE in lipid regulation via apolipoprotein B (APOB) and apolipoprotein E (APOE), and in inflammation. The serum proteins were profiled using the aptamer-based Somalogic technology. Here, we validate and expand the serum protein signature of APOE using a combination of mass-spectrometry, ELISA, Luminex, antibody-based Olink proteomics, and blood transcriptomics. We replicate the association between APOB and the e2 allele of APOE, we correct the pattern of association between APOE genotypes and serum level of APOE, and we detect new associations between APOE genotypes and the complex of apolipoproteins APOC1, APOC4, APOC2, APOC3, APOE, APOF and APOL1. In addition, we discover 13 new proteins that correlate with APOE genotypes. This extended signature includes granule proteins CAMP, CTSG, DEFA3, and MPO secreted from neutrophils and points to olfactomedin 4 (OLFM4) as a new target for the prevention of Alzheimers disease.

genetics↗

bioRxiv2025

Proteomic profiling of zinc homeostasis mechanisms in Pseudomonas aeruginosa through data-dependent and data-independent acquisition mass spectrometry

Zinc is central to the function of many proteins, yet the mechanisms of zinc homeostasis and their interplay with other cellular systems remain underexplored. In this study, we employ data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to investigate proteome changes in Pseudomonas aeruginosa under conditions of different zinc availability. Using these methods, we detected 2143 unique proteins, 1578 of which were identified by both DDA and DIA. We demonstrated that most of the previously described Zn homeostasis systems exhibit proteomic responses that follow similar trends to those seen in transcriptomics studies. However, some proteins that are considered instrumental in Zn homeostasis, notably those in Zn transporter ZnuABC, were not detected by our methods, although other proteins of other uptake systems were abundant. Furthermore, changes in abundance of multiple Zn-metalloproteins and Zn-independent homologs were clearly observable, with respective increases and decreases when Zn was provided, though the magnitude of these changes varied. Most of the Zn-metalloproteins observed were located in one of two Zur-regulated operons between PA5534 and PA5541. This study provides a view of Zn homeostasis mechanisms that is complementary to existing transcriptomics investigations: as gene transcripts are not strictly proportional to the actual distribution of proteins within a cell, analysis of the proteome offers another way to assess the relative use and importance of similar or ostensibly redundant systems in different conditions and can highlight shifts in metal prioritization between metalloproteins.

microbiology↗

bioRxiv2024

Transcriptional landscape of the archaeal cell cycle is broadly conserved in eukaryotes

The cell cycle is a series of events that occur from the moment of cell birth to cell division. In eukaryotes, cell growth, genome replication, genome segregation, and cytokinesis are strictly coordinated, defining discrete cell cycle phases. In contrast, these key processes may occur concurrently in bacteria. Thermoacidophilic archaea in the genus Saccharolobus follow a defined cell cycle program, with the first pre-replicative growth (G1) phase, followed by the chromosome replication (S) phase, the second growth (G2) phase, and rapid genome segregation (M) and cytokinesis (D) phases. However, whether other processes, such as metabolism, catabolism, protein translation, and antiviral defense also occur at specific cell cycle phases, as in eukaryotes, or are active throughout the cell cycle, as in bacteria, remains unclear. To address this question, we synchronized cultures of S. islandicus and performed an in-depth transcriptomic analysis of samples enriched in cells undergoing the M-G1, S, and G2 phases. Differential gene expression and consensus gene co-expression network analyses provided a holistic view of the S. islandicus cell cycle. In addition to the core transcriptome network, which is expressed throughout the cell cycle, we show that diverse metabolic pathways, protein synthesis, cell motility and even antiviral defense systems, are expressed in a cell cycle dependent fashion. Our data also refines understanding of the processes previously known to be linked to the cell cycle, such as DNA replication. We show that most DNA replication genes are expressed prior to the S phase, during the M-G1, whereas expression of the major chromatin genes, and accordingly, chromatinization are concomitant with replication. A statistical model was used to define sets of signature genes characteristic of each of the analyzed cell cycle phases, emphasizing transcriptional stratification of the phases. Signature genes are more conserved across Thermoproteota than non-signature genes and their peak expression, especially for the M-G1 and G2 specific genes, matches that of homologs in yeast. Collectively, our data elucidate the complexity of the S. islandicus cell cycle and suggest that it more closely resembles the cell cycle of eukaryotes than previously appreciated.

microbiology↗

bioRxiv2024

Social information use across trophic guilds

Animals use social information gathered by observing other individuals to adjust their behavior to better match the environment and improve fitness. Many insects use social information in various contexts. Bees improve their foraging efficiency by using social information from conspecifics to gauge nectar availability. Bees frequently encounter various heterospecific flower visitors, including those from different trophic groups such as nectaring predators. These heterospecifics may provide valuable information about nectar availability. We determined how bumble bees (Bombus impatiens) use visual social information from lady beetles (Hippodamia convergens). Lady beetles are predators of small insects, but not bees, and also visit flowers to consume floral nectar to increase their reproductive output. Using laboratory-maintained bumble bees freely flying in arenas, we tested if bees could (1) innately recognize lady beetles as sources of social information about nectar, and (2) learn to use lady beetles to gauge nectar availability. Bees did not innately recognize lady beetles as a source of social information. They correctly learned to associate conspecifics with the presence and absence of food, but learned to associate lady beetles only with the presence of food and not the absence. Our results demonstrate social learning across species and trophic guilds, but suggest limits to when and how bees generalize social information from diverse heterospecific flower visitors.

animal behavior and cognition↗

bioRxiv2024

Cross-platform proteomics signatures of extreme old age

In previous work we used a Somalogic platform targeting approximately 5000 proteins to generate a serum protein signature of centenarians that we validated in independent studies that used the same technology. We set here to validate and possibly expand the results by profiling the serum proteome of a subset of individuals included in the original study using liquid chromatography tandem mass spectrometry (LC-MS/MS). Following pre-processing, the LC-MS/MS data provided quantification of 398 proteins, with only 266 proteins shared by both platforms. At 1% FDR statistical significance threshold, the analysis of LC-MS/MS data detected 44 proteins associated with extreme old age, including 23 of the original analysis. To identify proteins for which associations between expression and extreme-old age were conserved across platforms, we performed inter-study conservation testing of the 266 proteins quantified by both platforms using a method that accounts for the correlation between the results. From these tests, a total of 80 proteins reached 5% FDR statistical significance, and 26 of these proteins had concordant pattern of gene expression in whole blood. This signature of 80 proteins points to blood coagulation, IGF signaling, extracellular matrix (ECM) organization, and complement cascade as important pathways whose protein level changes provide evidence for age-related adjustments that distinguish centenarians from younger individuals.

bioinformatics↗

bioRxiv2024

Network studies unveil new groups of highly divergent proteins in families as old as cellular life with important biological functions in the ocean

BackgroundMetagenomics has considerably broadened our knowledge of microbial diversity, unravelling fascinating adaptations and characterising multiple novel major taxonomic groups, e.g. CPR bacteria, DPANN and Asgard archaea, and novel viruses. Such findings profoundly reshaped the structure of the known tree of life and emphasised the central role of investigating uncultured organisms. However, despite significant progresses, a large portion of proteins predicted from metagenomes remain today unannotated, both taxonomically and functionally, across many biomes and in particular in oceanic waters, including at relatively lenient clustering thresholds. ResultsHere, we used an iterative, network-based approach for remote homology detection, to probe a dataset of 40 million ORFs predicted in marine environments. We assessed the environmental diversity of 53 gene families as old as cellular life, broadly distributed across the Tree of Life. About half of them harboured clusters of environmental homologues that diverged significantly from the known diversity of published complete genomes, with representatives distributed across all the oceans. In particular, we report the detection of environmental clades with new structural variants of essential genes (SMC), divergent polymerase subunits forming deep-branching clades in the polymerase tree, and variant DNA recombinases of unknown origin in the ultra-small size fraction. ConclusionsThese results indicate that significant environmental diversity may yet be unravelled even in strongly conserved gene families. Protein sequence similarity network approaches, in particular, appear well-suited to highlight potential sources of biological novelty and make better sense of microbial dark matter across taxonomical scales.

evolutionary biology↗

bioRxiv2023

Characterisation and reprogramming of bacteriophage mv4 integrase recombination specificity

Bacteriophage mv4 is a temperate bacterial virus able to integrate its genome at the 3 end of the tRNASER of Lactobacillus delbrueckii subsp. bulgaricus chromosome through site-specific recombination. Previous investigations revealed that the mv4Int/attP/attB recombination module was atypical compared to conventional heterobivalent tyrosine recombinases, such as the paradigmatic Lambdavirus lambda integrase, suggesting alternative recombination mechanism. In vitro recombination assays with random DNA libraries were used to comprehensively delineate the mv4 recombination system. We showed that mv4Int is a 369-aa protein that exhibits all structural hallmarks of integrases from the Tn916 family and interacts cooperatively with its recombination sites. We established that mv4Int distinguishes itself from classical heterobivalent integrases by a greater tolerance to nucleotide variations in attB and core-attP sites. We demonstrated that, upon considering nucleotide degeneracy, the 21-bp core-attP and attB recombination sites share structural similarities with classical heterobivalent integrase systems, with two 7-bp inverted-repeat regions corresponding to mv4Int core-binding sites surrounding a 7-bp strand-exchange region. Furthermore, our study highlighted compositional biases and nucleotide interdependencies within the core-binding regions that exerted a significant influence on the outcomes of recombination events.

molecular biology↗

bioRxiv2023

Prioritized imputed sequence variants from multi-population GWAS improve prediction accuracy for sea lice count in Atlantic salmon (Salmo salar)

Sea lice infestation is one of the major fish health problems during the grow-out phase in Atlantic salmon (Salmo salar) aquaculture. In this study, we integrated different genomic approaches, including whole-genome sequencing (WGS), genotype imputation and meta-analysis of genome-wide association studies (GWAS), to identify single-nucleotide polymorphisms (SNPs) associated with sea lice count in Atlantic salmon. Different sets of trait-associated SNPs were prioritized and compared against randomly chosen markers, based on the accuracy of genomic predictions for the trait. Lice count phenotypes and dense genotypes of five breeding populations challenged against sea lice were used. Genotype imputation was applied to increase SNP density of challenged animals to WGS level. The summary statistics from GWAS of each population were then combined in a meta-analysis to increase the sample size and improve the statistical power of associations. Eight different genotyping scenarios were considered for genomic prediction: 70K_array: 70K standard genotyping panel; 70K_priori: 70K SNPs with the highest p-values identified in the meta-analysis; 30K_priori: 30K SNPs with the highest p-values identified in the meta-analysis; WGS: SNPs imputed to whole-genome sequencing level; and the remaining four scenarios were the same SNP sets with a linkage disequilibrium (LD) pruning filter: 70K_array_LD; 70K_priori_LD; 30K_priori_LD and WGS_LD, respectively. Genomic prediction accuracy was evaluated using a five-fold cross-validation scheme in two different populations excluding them from the meta-analysis to remove possible validation-reference bias. Results showed significant genetic variation for sea lice counting in Atlantic salmon across populations, with heritabilities ranging from 0.06 to 0.24. The meta-analysis identified several SNPs associated with sea lice resistance, mainly in Ssa03 and Ssa09 chromosomes. Genomic prediction using the GWAS-based prioritized SNPs showed higher accuracy compared to using the standard SNP array in most of scenarios, achieving up to 57% increase in accuracy. Accuracy of prioritized scenarios was higher for the 70K_priori in comparison to 30K_priori. The use of WGS data in genomic prediction presented marginal or negative accuracy gain compared to the standard SNP array. The LD-pruning filter presented no benefits, reducing accuracy in most of scenarios. Overall, our study demonstrated the potential of prioritized of imputed sequence variants from multi-population GWAS meta-analysis to improve prediction accuracy for sea lice count in Atlantic salmon. The findings suggest that incorporating WGS data and prioritized SNPs from GWAS meta-analysis can accelerate the genetic progress of selection for polygenic traits in salmon aquaculture.

genomics↗

bioRxiv2022

GWAS meta-analysis of resistance against Piscirickettsia salmonis in Atlantic salmon

Salmonid rickettsial syndrome (SRS) remains as one of the most important pathogens for salmon farming. Genetic improvement has proven to be a viable alternative to reduce mortality in breeding stock. Understanding the genetic architecture of resistance has been a matter of ongoing research aimed at establishing the most appropriate method by which genomic information can be incorporated into breeding programs. However, the genetic architecture of complex traits such as SRS resistance may vary due to genetic and environmental background. In this work, we used the genotypes of a total of 5839 Atlantic salmon from 4 different experimental challenges against Piscirickttsia salmonis, which were imputed high density ([~]930K SNP) to perform within-population genomic-association analyses, followed by a meta-analysis of resistance to SRS defined as binary survival and day of death. The objectives of this study were to i) uncover the genomic regions associated with resistance to SRS among multiple populations; and ii) identify candidate genes associated with each trait definition. SNP-based meta-analysis revealed a clear QTL on Ssa02 for both traits while gene-based meta-analysis revealed 16 genes in common for both traits. Our results suggest a polygenic genetic architecture and provide novel insights into the candidate genes underpinning resistance to P. salmonis in Salmo salar.

genomics↗

bioRxiv2022

ADeS: a deep learning based Apoptosis Detection System for live cell imaging.

Intravital microscopy has revolutionized live cell imaging by allowing the study of spatial-temporal cell dynamics in living animals. However, the complexity of the data generated by this technology has limited the development of effective computational tools to identify and quantify cell processes. Amongst them, apoptosis is a crucial form of regulated cell death involved in tissue homeostasis and host defense. Live-cell imaging enabled the study of apoptosis at the cellular level, enhancing our understanding of its spatial-temporal regulation. However, at present, no computational method can deliver robust detection of apoptosis in microscopy time-lapses. To overcome this limitation, we developed ADeS, a deep learning-based apoptosis detection system that employs the principle of activity recognition. We trained ADeS on extensive datasets containing more than 10,000 apoptotic instances collected both in vitro and in vivo, achieving a classification accuracy above 98% and outperforming state-of-the-art solutions. ADeS is the first method capable of detecting the location and duration of multiple apoptotic events in full microscopy time-lapses, surpassing human performance in the same task. We demonstrated the effectiveness and robustness of ADeS across various imaging modalities, cell types, and staining techniques. Finally, we employed ADeS to quantify cell survival in vitro and tissue damage in vivo, demonstrating its potential application in toxicity assays, treatment evaluation, and inflammatory dynamics. Our findings suggest that ADeS is a valuable tool for the accurate detection and quantification of apoptosis in live-cell imaging and, in particular, intravital microscopy data, providing insights into the complex spatial-temporal regulation of this process.

bioinformatics↗

bioRxiv2022

Meta-analysis of GWAS for sea lice load in Atlantic salmon

Sea lice (Caligus rogercresseyi) is an ectoparasite that causes major production losses in the salmon aquaculture industry of the southern hemisphere. Atlantic salmon (Salmo salar) is an important salmonid for the aquaculture industry and a species which is highly susceptible to sea lice infestation. Genetic variation for resistance to sea lice, defined as parasite load, has been found in Atlantic salmon. In addition, sea lice load has been shown to be a polygenic trait, controlled by several quantitative trait loci (QTL) which have small to medium effect, making them difficult to map with sufficient statistical power when sample sizes are limited. The use of medium density single nucleotide polymorphisms (SNP) can also adversely affect the success of identifying genetic variants significantly associated to sea lice load. In order to improve the ability to detect QTL significantly associated to sea lice load, we combined genotype imputation from medium- to high SNP-density and performed genome-wide association studies (GWAS) across different populations of Atlantic salmon. The imputation of genotypes of 6,144 fish challenged against sea lice from four year-classes was performed to increase density from 70K SNPs to 600K SNPs. A meta-GWAS was then carried out for three different traits: lice count, lice density and log-lice density. Using this approach, we detected a genomic region highly associated to sea lice load on Atlantic salmon chromosomes (ssa) 3 and 12 pronounced peaks and several other regions surpassing the significance threshold across almost all other chromosomes. We also identified important genes within the QTL regions, many of these genes are involved in tissue reparation, such as Mucin-16-like isoform X2 and Filamentous growth regulator 23-like isoform X1. The QTL region on ssa03 also contained cytoskeletal-modifying and immune response related genes such as Coronin 1A and Claudin. Our results confirm the highly polygenic architecture of sea lice load, but they also show that high experimental power can lead to the identification of candidate genes and thus to increased insight into the biology of sea lice resistance in Altantic salmon.

genomics↗

bioRxiv2022

Heavy metals in moss guide environmental justice investigation: a case study using community science in Seattle, WA, USA

Heavy metals concentrations often vary at small spatial scales not captured by air monitoring networks, with implications for environmental justice in industrial-adjacent communities. Pollutants measured in moss tissues are commonly used as a screening tool to guide use of more expensive resources, like air monitors. Such studies, however, rarely address environmental justice issues or involve the residents and other decision-makers expected to utilize results. Here, we piloted a community science approach, engaging over 55 people from nine institutions, to map heavy metals using moss in two industrial-adjacent neighborhoods. This area, long known for disproportionately poor air quality, health outcomes, and racial inequities, has only one monitor for heavy metals. Thus, an initial understanding of spatial patterns is critical for gauging whether, where, and how to invest further resources towards investigating heavy metals. Local youth led sampling of the moss Orthotrichum lyellii from trees across a 250x250-m sampling grid (n = 79) and generated data comparable to expert-collected samples (n = 19). We mapped 21 chemical elements measured in moss, including 6 toxic priority metals: arsenic, cadmium, chromium, cobalt, lead, and nickel. Compared to other urban O. lyellii studies, local moss had substantially higher priority metals, especially arsenic and chromium, encouraging community members to investigate further. Potential hotspots of priority metals varied somewhat but tended to peak near the central industrial core where many possible emissions sources, including legacy contamination, converge. Informed by these findings, community members successfully advocated regulators for a second study phase - a community-directed air monitoring campaign to evaluate residents exposure to heavy metals - as is needed to connect moss results back to the partnerships core goal of understanding drivers of health disparities. This follow-up campaign will measure metals in the PM10 fraction owing to clues in the current study that airborne soil and dust may be locally important carriers of priority metals. Future work will address how our approach combining bioindicators and community science ultimately affects success addressing longstanding environmental justice concerns. For now, we illustrate the potential to co-create new knowledge, to help catalyze and strategize next steps, in a complex air quality investigation.

scientific communication and education↗

bioRxiv2021

RRNPP_detector: a tool to detect RRNPP quorum sensing systems in chromosomes, plasmids and phages of gram-positive bacteria

Gram-positive bacteria (e.g. Firmicutes) and their mobile genetic elements (plasmids, bacteriophages) encode peptide-based quorum sensing systems (QSSs) that regulate behavioral transitions in a density-dependent manner. In their simplest form, termed "RRNPP", these QSSs are composed of two adjacent genes: a communication propeptide and its cognate intracellular receptor. Despite the prime importance of RRNPP QSSs in the regulation of key biological pathways such as virulence, sporulation or biofilm formation in bacteria, conjugation in plasmids or lysogeny in temperate bacteriophages, no tools exist to predict their presence in target genomes/mobilomes. Here, we introduce RRNPP_detector, a software to predict RRNPP QSSs in chromosomes, plasmids and bacteriophages of gram-positive bacteria, available at https://github.com/TeamAIRE/RRNPP_detector. RRNPP_detector does not rely on homology searches but on a signature of multiple criteria, which are common between distinct families of experimentally-validated RRNPP QSSs. Because this signature is generic while specific to the canonical mechanism of RRNPP quorum sensing, it enables the discovery of novel RRNPP QSSs and thus of novel "languages" of biocommunication. Applying RRNPP_detector against complete genomes of viruses and Firmicutes available on the NCBI, we report a potential 7.5-fold expansion of RRNPP QSS diversity, alternative secretion-modes for certain candidate QSS propeptides, bilingual bacteriophages and plasmids, as well as predicted chromosomal and plasmidic Biosynthetic-Gene-Clusters regulated by QSSs.

bioinformatics↗