Biology subjects

Barman, P.

Publications and source records attributed to Barman, P..

5 recordsLinked to original sources

bioRxiv2026

Nitrotoxin metabolism in bacteria may have emerged from a diverse oxidoreductase reservoir

Bacterial transformation of 3 nitropropionic acid (3NPA) is typically viewed through canonical nitronate monooxygenases (NMOs), yet sequence annotation poorly resolves function across this flavoprotein family. Here we show that the environmental YrpB/NMO associated oxidoreductase space is dominated by YrpB related proteins: across 13 metagenomes, 83.1% of 390 conserved domain supported candidates were YrpB-associated. Cultivation along an Eisenia fetida feed gut cast continuum recovered 31 phylogenetically diverse 3NPA responsive bacteria, revealing that this phenotype is distributed across multiple lineages. Using the previously genome-sequenced Serratia sp. EWG9 as a tractable exemplar, we demonstrate sustained 3NPA supported growth, 44% parent compound depletion and a broad early transcriptional reorganization. Its focal oxidoreductase OXR01 occupies overlapping YrpB/NMO sequence space and shows stable predicted 3NPA accommodation without strong transcriptional induction. These findings reposition canonical NMOs as one component of a broader, ecologically distributed oxidoreductase reservoir for bacterial nitrotoxin responsiveness.

microbiology↗

bioRxiv2026

Convergent genomic variation and wild-type composite RNA-seq profiling identify candidate modules associated with 3-nitropropionic acid utilization in Leclercia barmai

3-Nitropropionic acid (3-NPA) is a toxic nitroaliphatic compound, but the genomic basis of bacterial adaptation to 3-NPA remains incompletely resolved, especially in organisms lacking a canonical nitronate monooxygenase. Here, we used phenotype screening, whole-genome resequencing, targeted UHPLC-MS/MRM, and composite RNA-seq profiling to investigate 3-NPA utilization in Leclercia barmai EMC7. Following attempted Tn5-Mob mutagenesis and kanamycin-based recovery, two independently derived mutants, LTM01 and LTM14, showed impaired growth under 3-NPA-dependent minimal conditions. No stable transposon insertion was detected in either mutant. Comparative genome analysis instead revealed convergent loss-of-function (LOF) mutations affecting amino acid metabolism, nitrogen allocation, central carbon metabolism, cofactor-linked functions, transport, and metal-redox homeostasis, while the predicted flavin-dependent nitro-redox candidate and canonical nitrate/nitrite reduction loci were not disrupted. Targeted UHPLC-MS/MRM analysis showed that wild-type EMC7 depleted approximately 50% of 3-NPA within 36 h, whereas the mutants displayed poor 3- NPA-utilization phenotypes under the same growth framework. Wild-type RNA-seq under glucose-3NPA relative to glucose-KNO3 identified a broad expression profile involving flavin-redox functions, nitrogen assimilation, oxidative-stress response, envelope stress, efflux, cofactor metabolism, and iron homeostasis. Integration of mutant LOF profiles with wild-type gene expression data showed that several disrupted genes or functional counterparts belonged to modules showing expression changes during the wild-type glucose-3NPA response. These findings identify candidate adaptive modules associated with 3-NPA utilization in EMC7, including nitrogen redistribution, carbon entry, sulfur-redox support, cofactor supply, transport, envelope remodeling, and metal-redox control. These results extend the landscape of metabolic adaptation beyond canonical pathways in environmental bacteria.

microbiology↗

bioRxiv2026

A Two-Arm Metabolic-Efflux Adaptation Framework in Klebsiella pneumoniae under Mixed Pharmaceutical Exposure: rutA-Linked Oxidative Entry and rutR-Associated Regulation

Chemically complex pharmaceutical mixtures in wastewater and sludge can affect microbial adaptation; however, the responses to different co-occurring compounds have not been elucidated well. In this study, the adaptation of a strain derived from hospital sludge, Klebsiella pneumoniae SS02, to 17-ethinylestradiol (EE2), warfarin sodium, and their combination has been studied. The organism grows under all three conditions, and pre-exposure experiments show induction and cross-induction to substrates. UHPLC MS/MS analyses demonstrated that there is conditional depletion of the parent compound EE2 by [~]15% at 36 h post-treatment compared to initial concentrations, but not for the abiotic and non-adapted controls. The rate of warfarin sodium depletion was approximately [~]30% within 36 h and was in accordance with first order kinetics (k = 0.0102 /h; t{square}/{square}= 67.9 h). Under the combined treatment regime, there was a delay in warfarin sodium depletion, suggesting staged substrate consumption. Growth inhibition with efflux inhibitors confirmed transport-driven tolerance. A genome-based study revealed the coordinated response strategy that involved a proposed flavin-dependent monooxygenase (RutA), an oxidative entry into the pathway; redox processing linked to Hpa; aromatic metabolism through {beta}-ketoadipate pathway; and RND efflux system. The structural study additionally supported ligand-mediated decrease in DNA binding affinity of RutR, which is in agreement with de-repression of the substrate-activated regulatory mechanism. All these findings lead to the development of a dual-strategy for adaptation model in which oxidative modification and efflux-mediated protection work together under the influence of a mixture of pharmaceuticals.

microbiology↗

bioRxiv2023

Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-worn Sensor: Performance Characterization Study

Background/ObjectivesMobility is a meaningful aspect of an individuals health whose quantification can provide clinical insights. Wearable sensor technology can quantify walking behaviors (a key aspect of mobility) through continuous passive monitoring. Our objective was to characterize the accuracy and reliability performance of a suite of digital measures of walking behaviors, as critical aspects in the practical implementation of digital measures into clinical studies. MethodsWe collected data from a wrist-worn device (the Verily Study Watch) worn for multiple days by a cohort of volunteer participants without history of gait/walking impairment in a real world setting. Based on step measurements computed in 10-second epochs from sensor data, we generated individual daily aggregates (participant-days) to derive a suite of measures of walking: step count, walking bout duration, number of total walking bouts, number of long walking bouts, number of short walking bouts, peak 30-minute walking cadence, peak 30-minute walking pace. To characterize accuracy of the measures, we examined agreement with truth labels generated by a concurrent, ankle-worn, reference device (Modus StepWatch 4) with known low error, calculating the following metrics: Intraclass Correlation Coefficient (ICC), Pearson R, Mean Error (ME), Mean Absolute Error (MAE). To characterize the reliability, we developed a novel approach to identify the time to reach a reliable readout (time-to-reliability) for each measure. This was accomplished by computing mean values over aggregation scopes ranging from 1-30 days, and analyzing test-retest reliability based on ICCs between adjacent (non-overlapping) time windows for each measure. ResultsIn the accuracy characterization, we collected data for a total of 162 participant-days from a testing cohort (N=35 participants; median observation time, 5 days). Agreement with the reference device-based readouts in the testing subcohort (n=35) for the eight measurements under evaluation, as reflected by ICCs, ranged between 0.7-0.9; Pearson R values were all greater than 0.75. For the time-to-reliability characterization, we collected data for a total of 15,120 participant days (overall cohort N=234; median observation time, 119 days). Here, all digital measures achieved an ICC between adjacent readouts > 0.75 by 16 days of wear time. ConclusionsWe characterized accuracy and reliability of a suite of digital measures that provides comprehensive information about walking behaviors in real-world settings. These results, which report the level of agreement with high-accuracy reference labels and the time duration required to establish reliable measure readouts, can guide practical implementation of these measures into clinical studies. Well-characterized tools to quantify walking behaviors in research contexts can provide valuable clinical information about general population cohorts and patients with specific conditions.

bioinformatics↗

bioRxiv2017

Sepsis: Partial least squares structural equation modelling (PLS-SEM) suggests a critical role for anti-inflammatory responses in clinical severity

BackgorundDespite major advances in medicine, Sepsis remains one of the major killers in critical care wards around the world. For several years it was widely believed that an early pro-inflammatory host response is followed by an overwhelming anti-inflammatory phase. The hypo-inflammatory status, termed as Compensatory anti-inflammatory response syndrome (CARS), was proposed to be the primary cause of sepsis-associated mortality. However, this paradiam changed in recent years since there was little evidence to support the linear model of host response and pathogenesis in sepsis. Currently held view is that both inflammatory and anti-inflammatory host responses are stimulated in an overlapping manner. In this study a robust statistical model to study the complex interplay of host cytokines in human sepsis has been developed to evaluate host responses in sepsis that contribute significantly to clinical pathology.\n\nMethodsTwentyseven cytokines/ chemokines were quantified in 139 sepsis patients and multivariate analysis of variance (MANOVA) was performed to assess differences in host responses in different categories of clinical severity. Partial least squares regression based structural equation modelling (PLS-SEM) was used to assess interactions between different groups of cytokines and their contribution to clinical pathology. An array of 23 cytokines was analysed in a mouse model of endotoxemia and a similar mathematical model was constructed.\n\nResultsThe results of MANOVA demonstrated the ability of combined cytokine response to discriminate sepsis patients according to clinical severity or outcome. Structural equation modelling revealed strong positive association between inflammatory and anti-inflammatory cytokines. In human sepsis, anti-inflammatory cytokines emerged as a significant entity associated with clinical severity as assessed by APACHE II scores.\n\nConclusionPLS-SEM modeling of cytokine responses and APACHE II score in human sepsis revealed that anti-inflammatory molecules contribute significantly towards clinical severity. More critically, the model offers emperical evidence for failures of clinical trials conducted during the last two decades in which antagonists of inflammatory host responses for human Sepsis were used for sepsis. The model also provides credence to the notion that inflammatory and anti-inflammatory host responses occur concurrently in both experimental endotoxemia and in human sepsis.

immunology↗