Biology subjects

Koduru, L.

Publications and source records attributed to Koduru, L..

5 recordsLinked to original sources

bioRxiv2026

Metabolic signals regulate resuscitation speed of antibiotic persister bacteria during infection

All living organisms adjust their metabolism in response to environmental changes. Under unfavorable conditions, organisms enter a state of dormancy by halting metabolism, enabling survival. Dormant bacteria become highly tolerant to antibiotics-a phenomenon called persistence. Here, we demonstrate that selective metabolic reprogramming controls the resuscitation speed of persister after antibiotic exposure. Using multi-omics and in silico modeling, we found that dormant bacteria reprogram metabolic pathways to modulate persister awakening. Accumulation of L-serine and reduction of arginine drive rapid resuscitation. L-serine promotes cysteine biosynthesis and motility while reducing energy metabolism to facilitate rapid resuscitation. In contrast, arginine slows regrowth from dormancy by enhancing ethanol-aldehyde and energy metabolism. L-serine and arginine can, respectively, promote or inhibit the regrowth of antibiotic persister cells in macrophages and mouse models, and regulate the awakening speed of Salmonella, E. coli, and methicillin-resistant Staphylococcus aureus (MRSA). These findings suggest new strategies to target chronic bacterial infections. TeaserL-serine speeds and arginine slows the awakening of antibiotic persisters, revealing targets for chronic infection.

microbiology↗

bioRxiv2024

FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models

Genome-scale metabolic models (GEMs) and other constraint-based models (CBMs) play a pivotal role in understanding biological phenotypes and advancing research in areas like metabolic engineering, human disease modelling, drug discovery, and personalized medicine. Despite their growing application, a significant challenge remains in ensuring the reproducibility of GEMs, primarily due to inconsistent reporting and inadequate model documentation of model results. Addressing this gap, we introduce FROG analysis, a community-driven initiative aimed at standardizing reproducibility assessments of CBMs and GEMs. The FROG framework encompasses four key analyses--Flux variability, Reaction deletion, Objective function, and Gene deletion--to produce standardized, numerically reproducible FROG reports. These reports serve as reference datasets, enabling model evaluators, curators, and independent researchers to verify the reproducibility of GEMs systematically. BioModels, a leading repository of systems biology models, has integrated FROG analysis into its curation workflow, enhancing the reproducibility and reusability of submitted GEMs. In our study evaluating 65 GEM submissions from the community, approximately 40% reproduced without intervention, 28% requiring minor adjustments, and 32% needing input from authors. The standardization introduced by FROG analysis facilitated the detection and resolution of issues, ultimately leading to the successful reproduction of all models. By establishing a standardized and comprehensive approach to evaluating GEM reproducibility, FROG analysis significantly contributes to making CBMs and GEMs more transparent, reusable, and reliable for the broader scientific community.

systems biology↗

bioRxiv2023

Expression and engineering of unexplored PET degrading enzymes from Microbispora, Nonomuraea, Micromonospora genus

Low recycling rates have resulted in the alarming rate of accumulation of a widely used plastic material, polyethylene terephthalate (PET). With the build-up of plastics in our environment, there is an urgent need to source for more sustainable solutions to process them. Biological methods such as enzyme-catalyzed PET recycling or bioprocessing are seen as a potential solution to this problem. Actinobacteria, known for producing enzymes involved in the degradation of complex organic molecules, are of particular interest due to their potential to produce PET degrading enzymes. The highly thermostable enzyme, leaf-branch compost cutinase (LCC) found in Actinobacteria is one such example. This work expands on the discovery and characterization of new PET degrading enzymes from Microbispora, Nonomuraea, and Micromonospora genus. Within this genus, we analyzed enzymes from the polyesterase-lipase-cutinase family, which have [~]60% similarity to LCC, where one of the enzymes was found to be capable of breaking down PET and BHET at 45-50 {degrees}C. Moreover, we were able to enhance the enzymes depolymerization rate through further engineering, resulting in a two-fold increase in activity. IMPORTANCEThe proliferation of PET plastic waste poses a significant threat to human and environmental health, making it an issue of increasing concern. In response to this challenge, scientists are investigating eco-friendly approaches, such as bioprocessing and microbial factories, to sustainably manage the growing quantity of plastic waste in our ecosystem. Despite the existence of enzymes capable of degrading PET, their scarcity in nature limits their applicability. The objective of this study is to enhance our understanding of this group of enzymes by identifying and characterizing novel ones that can facilitate the breakdown of PET waste. This data will expand the enzymatic repertoire and provide valuable insights into the prerequisites for successful PET degradation.

microbiology↗

bioRxiv2022

Cost-effective hybrid long-short read assembly delineates alternative GC-rich Streptomyces chassis for natural product discovery

With the advent of rapid automated in silico identification of biosynthetic gene clusters (BGCs), genomics presents vast opportunities to accelerate natural product (NP) discovery. However, prolific NP producers, Streptomyces, are exceptionally GC-rich (>80%) and highly repetitive within BGCs. These pose challenges in sequencing and high-quality genome assembly which are currently circumvented via intensive sequencing. Here, we outline a more cost-effective workflow using multiplex Illumina and Oxford Nanopore sequencing with hybrid long-short read assembly algorithms to generate high quality genomes. Our protocol involves subjecting long read-derived assemblies to up to 4 rounds of polishing with short reads to yield accurate BGC predictions. We successfully sequenced and assembled 8 GC-rich Streptomyces genomes whose lengths range from 7.1 to 12.1 Mb at an average N50 of 5.9 Mb. Taxonomic analysis revealed previous misrepresentation among these strains and allowed us to propose a potentially new species, Streptomyces sydneybrenneri. Further comprehensive characterization of their biosynthetic, pan-genomic and antibiotic resistance features especially for molecules derived from type I polyketide synthase (PKS) BGCs reflected their potential as NP chassis. Thus, the genome assemblies and insights presented here are envisioned to serve as gateway for the scientific community to expand their avenues in NP discovery. Graphic abstractSchematic of hybrid long- and short read assembly workflow for genome sequencing of GC-rich Streptomyces. Boxes shaded blue and grey correspond to experimental and in silico workflows, respectively. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/519232v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1395af0org.highwire.dtl.DTLVardef@81798forg.highwire.dtl.DTLVardef@539c92org.highwire.dtl.DTLVardef@14c366f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA cost-effective genome sequencing approach for GC-rich Streptomyces is presented C_LIO_LIHybrid assembly improves BGC annotation and identification C_LIO_LIA new species, Streptomyces sydneybrenneri, identified by taxonomic analysis C_LIO_LIGenomes of 8 Streptomyces species are reported and analysed in this study C_LI

genomics↗

bioRxiv2021

Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet-induced and strain-specific probiotic idiosyncrasies

Lactic acid bacteria (LAB) naturally occur in animal and plant niches and are well-known to elicit several health benefits in humans. Yet, how they adapt their functional metabolic landscapes to diverse nutrient environments and synthesize relevant bioactive compounds remain unexplored across genera, species and strains. Hence, presented herein is a systematic framework for comprehensively characterizing the genome-wide metabolisms of six representative LAB by combining multi-omics data with in silico modeling. We analyse the differences in their growth and cellular fitness, biosynthetic capability of health-relevant compounds, i.e., postbiotics, and probable interactions with 15 common gut microbiota under 11 virtual dietary regimes, and show such attributes are diet- and species-specific. Particularly, some LAB exhibit a desirable balance between synthesis of beneficial postbiotic compounds, positive interactions with beneficial gut commensals, and the ability to colonize and persist in gut environment. We also observe that "high fat-low carb" diets likely lead to detrimental outcomes in most LAB. Our results clearly highlight that probiotics are not "one size fits all" commodities and need to be formulated in a personalised manner for their use as dietary supplements and live biotherapeutics. Overall, the proposed framework will systematize the probiotic administration and could also widen the strain repertoire.

systems biology↗