Biology subjects

Ortiz-Marquez, J. C.

Publications and source records attributed to Ortiz-Marquez, J. C..

8 recordsLinked to original sources

bioRxiv2026

An Expanded Lpt Pathway Couples Surface Lipoprotein Export to Outer Membrane Vesicle Biogenesis in Bacteroides

The ecological dominance of Bacteroidota in the human gut microbiota derives from their exceptional capacity to metabolize diverse dietary and host-derived glycans. This ability relies on surface-exposed lipoproteins (SLPs), which are displayed on the bacterial surface and selectively packaged into outer membrane vesicles (OMVs). Although SLP export and OMV biogenesis are tightly coupled, the mechanism linking these processes has remained unknown. Here, we identify LptZ, a previously uncharacterized protein, as a critical link between SLP surface translocation and OMV biogenesis. Cryo-electron tomography of the lptZ mutant revealed chains of vesicles tethered to the outer membrane, offering a rare glimpse into an arrested stage of OMV formation in which vesicle fission is impaired. Proteomic analysis further showed that, in the absence of LptZ, a subset of SLPs fails to reach the cell surface and instead accumulates at the inner membrane. Unexpectedly, LptZ associates with the lipopolysaccharide transport (Lpt) machinery and repurposes it for SLP translocation. Crosslinking experiments revealed selective associations between multiple SLPs and Lpt proteins, providing mechanistic evidence for the direct involvement of the Lpt machinery in SLP trafficking. We further show that the Bacteroides Lpt machinery contains previously unrecognized components, revealing an unanticipated level of specialization relative to canonical Lpt systems. Together, our findings uncover a previously unknown protein export pathway, expand the functional role of the Lpt machinery, and establish a direct mechanistic link between SLP translocation and OMV biogenesis in Bacteroidota.

microbiology↗

bioRxiv2026

The transcriptional response of Yersinia pseudotuberculosis to macrophage-released chemicals during growth within synthetic microcolonies

Yersinia pseudotuberculosis (Yptb) replicates in immune cell-encompassed microcolonies within tissues. Bacterial replication is controlled by protection against neutrophil attack and by macrophage-released antimicrobial factors, such as nitric oxide (NO). During these attacks, bacteria located on the microcolony periphery encounter extracellular signals that differ from those in the interior. To dissect individual microbial populations, {gamma} interferon-activated macrophages were used to challenge microdroplet-grown Yptb harboring an NO-responsive mCherry reporter. Subsequently, bacterial subpopulations that hyperactivated the reporter were isolated from droplets composed of a reversible polymer matrix. RNA-seq analysis indicated that induction of nitrosative stress-associated genes was the primary determinant distinguishing peripheral bacteria from the remaining population. In addition, a secondary stress response that induced prophage-associated genes was detected, which could not be traced to either DNA damage or nitrosative stress responses. Activated macrophages also induced the expression of the Yptb itaconate degradation enzyme-encoding transcript throughout the entire colony. To determine if itaconate production by the interferon-activated Irg1 protein played a role in restricting Yptb, bacteria harboring an itaconate-responsive reporter and Yptb mutants defective for itaconate degradation were analyzed during bacterial colonization of the murine spleen. Only a subset of colonies appeared to be exposed to itaconate, which may explain the very small defects exhibited by mutants unable to degrade the interferon-induced macrophage product. These results indicate that the primary response of bacteria to macrophage-elicited factors is likely associated with protection against NO-derived metabolites.

microbiology↗

bioRxiv2025

Dual Membrane-spanning Anti-Sigma 2 Controls OMV biogenesis and Colonization Fitness in Bacteroides thetaiotaomicron

Bacteroides spp. are Gram-negative, gut commensals that shape the enteric landscape by producing outer membrane vesicles (OMVs) that degrade dietary fibers and traffic immunomodulatory biomolecules. Understanding the mechanism behind OMV biogenesis in Bacteroides spp. is necessary to determine their role in the gut. Recent studies showed that mutation of Dual Membrane-spanning Anti-sigma factor 1 increased OMV production in Bacteroides thetaiotaomicron (Bt) by regulating members of its downstream regulon. Additional members of the Dma family have been identified, but very little is known regarding their roles in Bt. Here, we investigate the role of Dual Membrane-spanning Anti-sigma factor 2 (Dma2) in controlling OMV biogenesis in Bt. We employ biochemical and proteomic analyses to show that mutation of dma2 increases OMV production in a manner that is dependent on the expression of its cognate sigma factor, das2. The precise mechanism by which dma2 increases OMV biogenesis remains elusive. However, transcriptome analyses revealed that{Delta} dma2 has decreased expression of select polysaccharide utilization loci (PULs) that primarily target host-associated glycans. Follow-up comparative proteomics showed that the PUL repertoire was most impacted in the OMV fraction. In vitro growth assessments showed that{Delta} dma2 exhibits delayed growth in the presence of select host-associated glycans. Colonization studies in mice revealed that{Delta} dma2 is outcompeted by the wild-type in the gut, which indicates that dma2 is a key determinant of colonization fitness in Bt. Altogether, these findings expand our knowledge of the Dma familys role in OMV biogenesis and demonstrates their importance in Bacteroides physiology. ImportanceDual membrane-spanning anti-sigma factors (Dma) are a novel class of regulatory system found solely amongst Bacteroidota. Previous studies have demonstrated the role of Dma1 in vesiculation, but the overall role of the Dma family in Bacteroides physiology remains poorly understood. Here, we demonstrate that Dma2 modulates vesiculation and regulates the expression of select polysaccharide utilization loci (PULs) that target host-associated glycans. In vivo studies revealed that Dma2 is an important fitness determinant when competing against kin bacteria. This work begins characterizing the multifaceted involvement of Dma2 in OMV biogenesis, PUL regulation, and colonization fitness.

microbiology↗

bioRxiv2024

Diclofenac sensitizes multi-drug resistant Acinetobacter baumannii to colistin

Acinetobacter baumannii causes life-threatening infections that are becoming difficult to treat due to increasing rates of multi-drug resistance (MDR) among clinical isolates. This has led the World Health Organization and the CDC to categorize MDR A. baumannii as a top priority for the research and development of new antibiotics. Colistin is the last-resort antibiotic to treat carbapenem-resistant A. baumannii. Not surprisingly, reintroduction of colistin has resulted in the emergence of colistin-resistant strains. Diclofenac is a nonsteroidal anti-inflammatory drug used to treat pain and inflammation associated with arthritis. In this work, we show that diclofenac sensitizes colistin-resistant A. baumannii clinical strains to colistin, in vitro and in a murine model of pneumonia. Diclofenac also reduced the colistin MIC of Klebsiella pneumoniae and Pseudomonas aeruginosa isolates. Transcriptomic and proteomic analyses revealed an upregulation of oxidative stress-related genes and downregulation of type IV pili induced by the combination treatment. Notably, the concentrations of colistin and diclofenac effective in the murine model were substantially lower than those determined in vitro, implying a stronger synergistic effect in vivo compared to in vitro. A pilA mutant strain, lacking the primary component of the type IV pili, became sensitive to colistin in the absence of diclofenac. This suggest that the downregulation of type IV pili is key for the synergistic activity of these drugs in vivo and indicates that colistin and diclofenac exert an anti-virulence effect. Together, these results suggest that the diclofenac can be repurposed with colistin to treat MDR A. baumannii.

microbiology↗

bioRxiv2021

Rapid, multianalyte detection of opioid metabolites in wastewater

By monitoring opioid metabolites, wastewater-based epidemiology (WBE) could be an excellent tool for real-time information on consumption of illicit drugs. A key limitation of WBE is the reliance on costly laboratory-based techniques that require substantial infrastructure and trained personnel, resulting in long turnaround times. Here, we present an aptamer-based graphene field effect transistor (AptG-FET) platform for simultaneous detection of three different opioid metabolites. This platform provides a reliable, rapid, and inexpensive method for quantitative analysis of opioid metabolites in wastewater (WW). The platform delivers a limit of detection (LOD) 2-3 orders of magnitude lower than previous reports, but in line with the concentrations range (pg/ml to ng/ml) of these opioid metabolites present in real samples. To enable multianalyte detection we developed a facile, reproducible, and high yield fabrication process producing twenty G-FETs with integrated side gate platinum (Pt) electrodes on a single chip. Our devices achieved the simultaneous and selective multianalyte detection of three different metabolites: Noroxycodone (NX), 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), and Norfentanyl (NF) in wastewater.

biophysics↗

bioRxiv2020

Detection of a multi-disease biomarker in Salivawith Graphene Field Effect Transistors

Human carbonic anhydrase 1 (CA1) has been suggested as a biomarker for identification of several diseases including cancers, pancreatitis, diabetes, and Sjogrens syndrome. However, the lack of a rapid, cheap, accurate, and easy-to-use quantification technique has prevented widespread utilization of CA1 for practical clinical applications. To this end, we present a label-free electronic biosensor for detection of CA1 utilizing highly sensitive graphene field effect transistors (G-FETs) as a transducer and specific RNA aptamers as a probe. The binding of CA1 with aptamers resulted in a positive shift in Dirac voltage VD of the G-FETs, the magnitude of which depended on target concentration. These aptameric G-FET biosensors showed the binding affinity (KD) of [~] 2.3 ng/ml (70 pM), which is four orders lower than that reported using a gel shift assay. This lower value of KD enabled us to achieve a detection range (10 pg/ml - 100 ng/ml) which is well in line with the clinically relevant range. These highly sensitive devices allowed us to further prove their clinical relevance by successfully detecting the presence of CA1 in human saliva samples. Utilization of this label-free biosensor could facilitate the early stage identification of various diseases associated with changes in concentration of CAs.

biophysics↗

bioRxiv2019

Rapid, selective and single cell electrical detection of antibiotic resistant bacteria

The rapid increase in antibiotic resistant pathogenic bacteria has become a global threat, which besides the development of new drugs, requires rapid, cheap, scalable, and accurate diagnostics. Label free biosensors relying on electrochemical, mechanical, and mass based detection of whole bacterial cells have attempted to meet these requirements. However, the trade-off between selectivity and sensitivity of such sensors remains a key challenge. In particular, point-of-care diagnostics that are able to reduce and/or prevent unneeded antibiotic prescriptions require highly specific probes with sensitive and accurate transducers that can be miniaturized and multiplexed, and that are easy to operate and cheap. Towards achieving this goal, we present a number of advances in the use of graphene field effect transistors (G-FET) including the first use of peptide probes to electrically detect antibiotic resistant bacteria in a highly specific manner. In addition, we dramatically reduce the needed concentration for detection by employing dielectrophoresis for the first time in a G-FET, allowing us to monitor changes in the Dirac point due to individual bacterial cells. Specifically, we realized rapid binding of bacterial cells to a G-FET by electrical field guiding to the device to realize an overall 3 order of magnitude decrease in cell-concentration enabling a single-cell detection limit, and 9-fold reduction in needed time to 5 minutes. Utilizing our new biosensor and procedures, we demonstrate the first selective, electrical detection of the pathogenic bacterial species Staphylococcus aureus and antibiotic resistant Acinetobacter baumannii on a single platform.

microbiology↗

bioRxiv2019

Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity.

Genes implicated in bacterial stress responses have been used to construct models that infer the growth outcome of a bacterium in the presence of antibiotics with the objective to develop novel diagnostic methods in the clinic. Current models are trained on data specific to a species or type of stress, making them potentially limited in their application. It is unclear if a generalizable response-signature exists that can predict bacterial fitness independent of strain, species or type of stress. Here we present a substantial RNA-Seq and experimental evolution dataset for 9 strains and species, under multiple antibiotic and non-antibiotic stress conditions. We show that gene panel-based models can accurately predict antibiotic mechanism of action, as well as the fitness outcome of Streptococcus pneumoniae in the presence of antibiotics or under nutrient depletion. However, these models quickly become species-specific as gene homology is limited. Instead, we define a new concept, transcriptomic entropy, which we use to quantify the amount of transcriptional disruption that occurs in a bacterium when responding to the environment. With entropy at the center, we train a suite of predictive (machine learning) models enabling generalizable fitness and antibiotic sensitivity predictions. These entropy-based models that predict bacterial fitness are validated for 7 Gram-positive and -negative species under antibiotic and non-antibiotic conditions indicating that transcriptomic entropy can be used as a generalizable stress signature. Moreover, rather than being a binary indicator of fitness, an entropy-based model was developed and validated to predict the minimum inhibitory concentration of an antibiotic. Lastly, we show that the inclusion of a varied-set of multi-omics features of a bacterial stress response further enhances fitness predictions by reducing ambiguity. By demonstrating the feasibility of generalizable predictions of bacterial fitness, this work establishes the fundamentals for potentially new approaches in infectious disease diagnostics, including antibiotic susceptibility testing.\n\nSignificance statementAccurate predictions of bacterial fitness outcome could potentially have clinical diagnostic value, such as predicting optimum antibiotic choice and dosage for treating infectious diseases. Existing models of fitness predictions rely mainly on gene panel approaches, which may be species- and stress-specific due to a lack of gene and response conservation. In order to overcome this limitation, we generated a substantial experimental dataset and identified entropy as a universal stress response signature that quantifies the level of transcriptional disruption that is indicative of fitness outcome under a stressful condition. We present and validate for Gram-positive and negative species a suite of entropy-based models that enable accurate predictions of fitness outcome and the level of antibiotic sensitivity in a species and stress-type independent manner.

systems biology↗