Biology subjects

Kushwaha, M.

Publications and source records attributed to Kushwaha, M..

10 recordsLinked to original sources

bioRxiv2026

Rapid Identification of Infections Directly from Isolates and Clinical Specimens with the MasSpec Pen Technology

The time-consuming nature of conventional bacterial identification methods, coupled with rising resistance to antibiotics, presents a serious challenge in the rapid diagnosis and treatment of patients suffering from severe infection and sepsis. In this study, we demonstrate that the MasSpec Pen (MSPen) technology enables rapid identification of the most frequently occurring bacterial species in human infections. A total of 755 clinical bacterial isolates prospectively collected from pediatric and adult patients were analyzed using the MSPen to create a library of molecular profiles. The mass spectra obtained presented distinct molecular patterns for bacterial species, with high relative abundances of bacterial metabolites and lipids, including unique quinolone signaling molecules in Pseudomonas aeruginosa, phosphoethanolamine (PE) lipids in Enterobacteriaceae, and phosphatidylglycerol (PG) lipids in Staphylococcus species. Logistic and multinomial lasso models using relative abundances or logarithmic-ratio abundance calculations achieved >95% accuracy for Gram stain typing and >92% for species-level identification in isolates. Random forest models yielded comparable performance, reinforcing the robustness of these findings across approaches. Many of the metabolite and lipid predictive features from each isolate classifier were detected when directly analyzing highly infected synovial fluid, tissue, pleural fluid, and breast aspirate specimens from patients. Notably, significant variations in the natural isotopic abundance of specific lipids were observed in infected patient samples, indicating presence of bacterial infection. This study demonstrates the potential of MSPen for the direct identification of bacterial-specific metabolites and lipids in clinical isolates and specimens, offering promise for future advancements in the MSPen technology for rapid bacterial identification. Teaser.MSPen shows potential for rapid, direct identification of bacterial metabolites and lipids, enabling accurate bacterial classification.

microbiology↗

bioRxiv2025

An M13 phagemid toolbox for engineering tuneable DNA communication in bacterial consortia

Intercellular communication is essential for distributed genetic circuits operating across cells in multicellular consortia. While diverse signalling molecules have been employed--ranging from quorum sensing signals, secondary metabolites, and pheromones to peptides, and nucleic acids--phage-packaged DNA offers a highly programmable method for communicating information between cells. Here, we present a library of five M13 phagemid variants with distinct replication origins, including those based on the Standard European Vector Architecture (SEVA) family, designed to tune the growth and secretion dynamics of sender strains. We systematically characterize how intracellular phagemid copy number varies with cellular growth physiology and how this, in turn, affects phage secretion rates. In co-cultures, these dynamics influence resource competition and modulate communication outcomes between sender and receiver cells. Leveraging the intercellular CRISPR interference (i-CRISPRi) system, we quantify phagemid transfer frequencies and identify rapid-transfer variants that enable efficient, low-burden communication. The phagemid toolbox developed here expands the repertoire of available phagemids for DNA-payload delivery applications and for implementing intercellular communication in multicellular circuits.

synthetic biology↗

bioRxiv2025

Chenodeoxycholic Acid Modulation via Bacteroides intestinalis AM1 underscores a Novel Approach in Acute Liver Failure

BackgroundAcute liver failure (ALF) is associated with rapid and progressive hepatocellular injury, and severe metabolic-microbial derangements. We investigated early metabolic markers of non-survival, and a potential microbial intervention using Bacteroides intestinalis-AM1, to improve outcomes in ALF. MethodPlasma metabolomics and meta-proteomics were performed in 40 ALF patients and 5 healthy controls (training cohort). A non-survival marker panel was identified and validated in 270 ALF patients (test cohort) using high resolution mass spectrometry and machine learning. It was functionally validated in acetaminophen-induced ALF mouse model. B. intestinalis-AM1 was used to study alteration of gut bacteria and amelioration of liver injury. ResultsALF non-survivors showed a distinct metabolomic signature with elevated primary bile acids {chenodeoxycholic acid (CDCA), cholic acid (CA)}, tryptophan, tyrosine, and enrichment of pathways linked to inflammation, cell death, and stress response (p<0.01, FDR<0.01, FC>1.5). Non-survivors had higher alpha/beta diversity (p<0.05) with increase in Proteobacteria, Firmicutes, Actinobacteria (p<0.05); functionally associated with energy, amino acid and xenobiotic metabolism (p<0.05). A gut microbiota derangement in converting primary to secondary bile acids was evident as CDCA and cytotoxic metabolites (4-(2-Amino phenyl)-2,4-dioxobutanoate, L-Tyrosine) were higher. Elevated CDCA (logFC>10) levels correlated with mortality in ALF patients as well as in mouse model. In the later, administration of B. intestinalis-AM1 bacteria, (10^9) reduced CDCA and CA levels by enhancing FXR, FGF15, SLC10A1 gene expression, attenuating inflammation (IL-1beta, TLR4-signalling), necroptosis, and modulating glutathione(oxidative-repair), tryptophan(inflammation), and histidine (tissue repair) metabolism. ConclusionHigh levels of chenodeoxycholic acid (CDCA) represent a poor prognostic indicator in ALF patients. B. intestinalis-AM1, a primary-to-secondary bile acid converter, effectively reduce CDCA levels, activated FXR, reduced inflammation and protected hepatocytes, highlighting its therapeutic potential in ALF.

microbiology↗

bioRxiv2024

Phage-mediated intercellular CRISPRi for biocomputation in bacterial consortia

Coordinated actions of cells in microbial communities and multicellular organisms enable them to perform complex tasks otherwise difficult for single cells. This has inspired biological engineers to build cellular consortia for larger circuits with improved functionalities, while implementing communication systems for coordination among cells. Here, we investigate the signalling dynamics of a phage-mediated synthetic DNA messaging system, and couple it with CRISPR interference to build distributed circuits that perform logic gate operations in multicellular bacterial consortia. We find that growth phases of both sender and receiver cells, as well as resource competition between them, shape communication outcomes. Leveraging the easy programmability of DNA messages, we build 8 orthogonal signals and demonstrate that intercellular CRISPRi (i-CRISPRi) regulates gene expression across cells. Finally, we multiplex the i-CRISPRi system to implement several multicellular logic gates that involve up to 7 cells and take up to 3 inputs simultaneously, with single- and dual-rail encoding: NOT, YES, AND, and AND-AND-NOT. The communication system developed here lays the groundwork for implementing complex biological circuits in engineered bacterial communities, using phage signals for communication.

synthetic biology↗

bioRxiv2022

Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides

Bioactive peptides are key molecules in health and medicine. Deep learning holds a big promise for the discovery and design of bioactive peptides. Yet, suitable experimental approaches are required to validate candidates in high throughput and at low cost. Here, we established a cell- free protein synthesis (CFPS) pipeline for the rapid and inexpensive production of antimicrobial peptides (AMPs) directly from DNA templates. To validate our platform, we used deep learning to design thousands of AMPs de novo. Using computational methods, we prioritized 500 candidates that we produced and screened with our CFPS pipeline. We identified 30 functional AMPs, which we characterized further through molecular dynamics simulations, antimicrobial activity and toxicity. Notably, six de novo-AMPs feature broad-spectrum activity against multidrug-resistant pathogens and do not develop bacterial resistance. Our work demonstrates the potential of CFPS for production and testing of bioactive peptides within less than 24 hours and <10$ per screen.

synthetic biology↗

bioRxiv2022

A synthetic communication system uncovers self-jamming of bacteriophage transmission

Understanding how delivery and exchange of genetic information by bacteriophages shapes bacterial populations is important for designing applications for phage therapy, biocontrol, and microbiome engineering. Here, we present a synthetic intercellular communication system that repurposes phage M13 for genetic exchange between Escherichia coli cells and build mathematical models of the communication behaviour. Our models, based on Chemical Reaction Networks, capture the growth burden, cell density, and growth phase dependence of phage secretion and infection kinetics and predict the stochasticity characterising phage-bacterial interactions at low numbers. In co-cultures of phage sender and receiver cells, resource sharing and selection pressure determine the choice of horizontal versus vertical phage transmission. Surprisingly, we discover that a phage-encoded immunity factor confers extracellular protection to uninfected bacteria, reducing infection rates by 70%. In a simulated gut environment, this novel "self-jamming" mechanism enables the phage to farm uninfected bacteria for future infections, increasing the overall success of both M13 and E. coli. The synthetic system developed here lays the groundwork for implementing population level controls in engineered bacterial communities, using phage signals for communication.

synthetic biology↗

bioRxiv2022

PeroxiHUB: a modular cell-free biosensing platform using H2O2 as signal integrator

Cell-free systems have great potential for delivering robust, cheap, and field-deployable biosensors. Many cell-free biosensors rely on transcription factors responding to small molecules, but their discovery and implementation still remain challenging. Here we report the engineering of PeroxiHUB, an optimized H2O2-centered sensing platform supporting cell-free detection of different metabolites. H2O2 is a central metabolite and a by-product of numerous enzymatic reactions. PeroxiHUB uses enzymatic transducers to convert metabolites of interest into H2O2, enabling rapid reprogramming of sensor specificity using alternative transducers. We first screen several transcription factors and optimize OxyR for the transcriptional response to H2O2 in cell-free, highlighting the need for pre-incubation steps to obtain suitable signal-to-noise ratios. We then demonstrate modular detection of metabolites of clinical interest - lactate, sarcosine, and choline - using different transducers mined via a custom retro-synthesis workflow publicly available on the SynBioCAD Galaxy portal. We find that expressing the transducer during the pre-incubation step is crucial for optimal sensor operation. Finally, we show that different reporters can be connected to PeroxiHUB, providing high adaptability for various applications. Given the wide range of enzymatic reactions producing H2O2, the PeroxiHUB platform will support cell-free detection of a large number of metabolites in a modular and scalable fashion.

synthetic biology↗

bioRxiv2022

Galaxy-SynBioCAD: Automated Pipeline for Synthetic Biology Design and Engineering

We introduce the Galaxy-SynBioCAD portal, the first toolshed for synthetic biology, metabolic engineering, and industrial biotechnology. The tools and workflows currently shared on the portal enables one to build libraries of strains producing desired chemical targets covering an end-to-end metabolic pathway design and engineering process from the selection of strains and targets, the design of DNA parts to be assembled, to the generation of scripts driving liquid handlers for plasmid assembly and strain transformations. Standard formats like SBML and SBOL are used throughout to enforce the compatibility of the tools. In a study carried out at four different sites, we illustrate the link between pathway design and engineering with the building of a library of E. coli lycopene-producing strains. We also benchmarked our workflows on literature and expert validated pathways. Overall, we find an 83% success rate in retrieving the validated pathways among the top 10 pathways generated by the workflows.

synthetic biology↗

bioRxiv2021

Differentially optimized cell-free buffer enables robust expression from unprotected linear DNA in exonuclease-deficient extracts

The use of linear DNA templates in cell-free systems promises to accelerate the prototyping and engineering of synthetic gene circuits. A key challenge is that linear templates are rapidly degraded by exonucleases present in cell extracts. Current approaches tackle the problem by adding exonuclease inhibitors and DNA-binding proteins to protect the linear DNA, requiring additional time- and resource-intensive steps. Here, we delete the recBCD exonuclease gene cluster from the Escherichia coli BL21 genome. We show that the resulting cell-free systems, with buffers optimized specifically for linear DNA, enable near-plasmid levels of expression from {sigma}70 promoters in linear DNA templates without employing additional protection strategies. When using linear or plasmid DNA templates at the buffer calibration step, the optimal potassium glutamate concentrations obtained when using linear DNA were consistently lower than those obtained when using plasmid DNA for the same extract. We demonstrate the robustness of the exonuclease deficient extracts across seven different batches and a wide range of experimental conditions across two different laboratories. Finally, we illustrate the use of the {Delta}recBCD extracts for two applications: toehold switch characterization and enzyme screening. Our work provides a simple, efficient, and cost-effective solution for using linear DNA templates in cell-free systems and highlights the importance of specifically tailoring buffer composition for the final experimental setup. Our data also suggest that similar exonuclease deletion strategies can be applied to other species suitable for cell-free synthetic biology.

synthetic biology↗

bioRxiv2019

Metabolic Perceptrons for Neural Computing in Biological Systems

AbstractSynthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a new approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model trained on experimental data, we finally implement two four-input \"perceptrons\" for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

synthetic biology↗