Biology subjects

Jayaraman, G.

Publications and source records attributed to Jayaraman, G..

12 recordsLinked to original sources

bioRxiv2026

Bioconversion of p-coumaric acid to cis,cis-muconic acid using an engineered A. baylyi ADP1 - E. coli co-culture

Lignin-derived aromatics are abundant in depolymerized lignin but remain remain untilized as carbon sources for commercial production of bulk chemicals. Among these aromatics, p-coumaric acid can be funnelled through the {beta}-ketoadipate pathway toward cis,cis-muconic acid (ccMA), a precursor of bio-based adipic and terephthalic acids. However, efficient ccMA production by Acinetobacter baylyi ADP1 is constrained by toxicity of catechol (the immediate precursor of ccMA), inefficient channelling of protocatechuate (PCA) metabolism towards ccMA production, and absence of PCA decarboxylase for converting PCA to catechol. Therefore, in this study, we engineered a modular co-culture system, combining engineered strains of A. baylyi and E. coli, for ccMA production from synthetic p-coumaric acid. Deletion of catB and catC genes and overexpression of catA in A. baylyi GJS_catA strain enabled near-stoichiometric conversion of catechol to ccMA ([~]90% carbon yield) with titres up to 56.4 mM ([~] 8 g/L) under controlled fed-batch feeding. The strain was further engineered (A. baylyi GJS2_catA) to convert p-coumaric acid to PCA. Due to the inactivity of heterologous PCA decarboxylase (aroY gene) in A. baylyi, this gene was incorporated in E. coli where it exhibited activity through PCA to catechol conversion. Upon its production by E.coli_aroY in the co-culture, catechol is instantaneously converted to ccMA by A. baylyi GJS2_catA strain. In a two-step process, 22 mM p-coumaric acid was initially converted to 20.6 mM PCA (A. baylyi GJS2_catA), which was further converted to catechol (E.coli_aroY) and finally to 18.55 mM ccMA (2.63 g L-{superscript 1}) by A. baylyi GJS2_catA. This process was validated by the valorization of lignin-derived p-coumaric acid to ccMA. While the modular strategy developed in this study substantially improves ccMA titres, it also highlights the bottlenecks in A. baylyi metabolic pathway engineering for lignin valorization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/709578v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@a83daborg.highwire.dtl.DTLVardef@168c6b6org.highwire.dtl.DTLVardef@1ce0abdorg.highwire.dtl.DTLVardef@23200b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

Epidural Thin Film Implants of Polymerized Curcumin Downregulate Inflammatory Markers and Improve Functional Recovery After Spinal Cord Injury in Mice

Spinal cord injury (SCI) is a notoriously intractable medical problem for which there is no neuroprotective pharmacotherapy, despite four decades of clinical trials on systemically administered small molecules that target plausible injury mechanisms. The shared failure mode of those trials is delivery: oxidative and inflammatory injury evolves locally at the lesion site over days to weeks, a timescale that far exceeds the half-life of systemically administered drugs. Furthermore, systemically administered drugs often cannot be dosed at high enough levels to achieve efficacious concentrations locally at the lesion site, without off-target effects. In this study, we show the first example of a locally implantable drug depot that exerts long-lasting activity at the lesion site. We demonstrate in vivo efficacy of a poly(pro-drug) thin film deployed locally, to address delivery problem in SCI. The films are composed of a copolyester in which curcumin, a potent natural antioxidant, is incorporated as a backbone repeat unit alongside poly(ethylene glycol) sebacate segments. The soft, thin film ([~]100 {micro}m) is employed as an epidural implant that quenches reactive oxygen species on-contact and can sustain activity for over two months, which is orders of magnitude longer than free curcumin (half-life of [~]10 min in buffer). A single epidural P50 film, placed on the exposed dura immediately after a moderate-to-severe T9 contusion in mice, produced a statistically significant improvement in Basso Mouse Scale locomotor recovery at 14 days post-injury, relative to a non-antioxidant control polymer of same architecture. The film preserved myelinated white matter, attenuated reactive gliosis (GFAP, Iba1), and produced coherent downregulation of neuroinflammatory gene-expression programs. These effects were spatially restricted to tissue rostral to the lesion, consistent with on-contact, locally confined polymer activity. Because curcumin is covalently enchained within the polymer itself, rather than blended as a payload in a carrier matrix, release is governed by backbone hydrolysis and the architecture can generalize to other phenolic bioactives, potentially establishing epidural poly(pro-drug) thin films as a mechanistically grounded, surgical platform for sustained local pharmacotherapy of CNS injury.

bioengineering↗

bioRxiv2024

A consortium-based approach to adaptive laboratory evolution of Acinetobacter baylyi ADP1 for lignin valorization

The utility of Acinetobacter baylyi ADP1 (ADP1) for lignin valorization has yet to be sufficiently investigated compared to other organisms such as Pseudomonas, Rhodococcus, etc. In this study, a two-step Adaptive Laboratory Evolution (ALE) process was used to evolve a unique ADP1 strain (A. baylyi SAG_185). Initially, several ADP1 strains were evolved for substrate tolerance to specific lignin-related aromatics (LRAs). Subsequently, a consortium of these strains was adaptively evolved in a mixture of LRAs, which resulted in the evolution of SAG_185. This strain was capable of simultaneous utilization of multiple LRAs at higher concentrations as well as grow on a depolymerized lignin-rich residue obtained from enzymatic hydrolysis of pre-treated corncob. This is the first report on such an evolutionary strategy. Whole-genome sequence analysis of all the evolved strains revealed large-scale mutations involving insertion sequences (IS). In particular, SAG_185 revealed a critical mutation in the vanR repressor gene, resulting in the up-regulation of vanAB genes required to convert vanillate to the key intermediate, protocatechuate (PCA). Additionally, there were two large deletions of 9kb and 38kb DNA segments, including genes for putative transcriptional regulators of LysR, MarR and AraC family. The evolved strains also showed mutations in the hcaE gene, responsible for the uptake of LRAs. The vast number of mutations in hypothetical proteins, transporter and regulatory sequences indicate the underlying effects of these regions on the uptake of multiple LRAs. Overall, our findings provide potential targets for reverse engineering of A. baylyi ADP1 for lignin valorization. IMPORTANCEThis study shows a novel strategy for adaptive laboratory evolution, which can be generically adopted to evolve bacterial strains for taking up multiple substrates which are toxic at higher concentrations. We developed a two-step evolutionary strategy to evolve a unique strain, A. baylyi SAG_185, which could take up multiple lignin-related aromatic monomers at higher concentrations as well as grow on depolymerized lignin. Initially, individual strains were adapted to utilize single aromatic monomers at higher concentrations. After many unsuccessful attempts to adapt these strains for utilizing multiple monomers, a consortium of the five evolved strains were grown on a mixture of aromatics and adapted to utilize all the monomers at high concentrations. The adapted consortia resulted in the evolution of SAG_185. Whole-genome sequence analysis of all these strains gave rise to many interesting insights on potential genetic targets for reverse engineering of A. baylyi ADP1 for lignin valorization.

microbiology↗

bioRxiv2023

Spinal Cord Injury regulates circular RNA expression in axons

IntroductionNeurons transport mRNA and translational machinery to axons for local translation. After spinal cord injury (SCI), de novo translation is assumed to enable neurorepair. Knowledge of the identity of axonal mRNAs that participate in neurorepair after SCI is limited. We sought to identify and understand how axonal RNAs play a role in axonal regeneration. MethodsWe obtained preparations enriched in axonal mRNAs from control and SCI rats by digesting spinal cord tissue with cold-active protease (CAP). The digested samples were then centrifuged to obtain a supernatant that were then sequenced. We used bioinformatics analyses to identify DEGS and map them to various biological processes. We validated the DEGs by RT-qPCR and RNA-scope. ResultsThe supernatant fraction was highly enriched for axonal mRNA. Using Gene Ontology, the second most significant pathway for all differentially expressed genes (DEGs) was axonogenesis. Among the DEGs was Rims2, which is predominately a circular RNA (circRNA) in the CNS. We show that Rims2 RNA within spinal cord axons is circular. We found an additional 200 putative circRNAs in the axonal-enriched fraction. Knockdown in primary rat cortical neurons of the RNA editing enzyme ADAR1, which inhibits formation of circRNAs, significantly increased axonal outgrowth. Focusing on Rims2 we used Circular RNA Interactome to predict that several of the miRNAs that bind to circRims2 also bind to the 3UTR of GAP-43, PTEN or CREB1, all known regulators of axonal outgrowth. Axonally-translated GAP-43 supports axonal elongation and we detect GAP-43 mRNA in the rat axons by RNAscope. DiscussionBy using our method for enrichment of axonal RNA, we detect SCI induced DEGs, including circRNA such as Rims2. Ablation of ADAR1, the enzyme that regulates circRNA formation, promotes axonal outgrowth of cortical neurons. We developed a pathway model using Circular RNA Interactome that indicates that Rims2 through miRNAs can regulate the axonal translation GAP-43 a known regulator of axonal regeneration indicating that axonal mRNA contribute to regeneration.

neuroscience↗

bioRxiv2021

Drug specific transcriptomic signatures in healthy human subject iPSC derived cardiomyocytes

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focused on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced pluripotent stem cell-derived cardiomyocytes. Using bulk transcriptomics profiles, we applied singular value decomposition to identify drug-selective patterns in cell lines obtained from multiple healthy human subjects. Cellular pathways affected by highly cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Whole genome sequences of the cell lines, using outlier responses enabled us to correctly reidentify a genomic variant associated with anthracycline cardiotoxicity and predict genomic variants potentially associated with TKI cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale predictive understanding of cardiotoxicity for drug development and patient stratification. One sentence summaryGenes, pathways, and cell types of the human heart associated with antineoplastic drug cardiotoxicity.

systems biology↗

bioRxiv2020

A Library Of Induced Pluripotent Stem Cells From Clinically Well-Characterized, Diverse Healthy Human Individuals

A library of well-characterized human induced pluripotent stem cell (hiPSC) lines from clinically healthy human subjects could serve as a useful resource of normal controls for in vitro human development, disease modeling, genotype-phenotype association studies, and drug response evaluation. We report generation and extensive characterization of a gender-balanced, racially/ethnically diverse library of hiPSC lines from 40 clinically healthy human individuals who range in age from 22-61. The hiPSCs match the karyotype and short tandem repeat identity of their parental fibroblasts, and have a transcription profile characteristic of pluripotent stem cells. We provide whole genome sequencing data for one hiPSC clone from each individual, genomic ancestry determination, and analysis of Mendelian disease genes and risks. We document similar transcriptomic profiles, single-cell RNA-seq derived cell clusters and physiology of cardiomyocytes differentiated from multiple independent hiPSC lines. This extensive characterization makes this hiPSC library a valuable resource for many studies on human biology.

cell biology↗

bioRxiv2020

In vivo single-cell analysis using calcofluor - white staining detects high expression phenotype in L. lactis cultures engineered for hyaluronic acid production.

Hyaluronic acid (HA) is a biopolymer with wide applications in the field of medicine and cosmetics. Bacterial production of HA has a huge market globally. Certain species of Streptococcus are native producers of HA but they are pathogenic. Therefore, safer organisms such as L. lactis are engineered for HA production. However, there are challenges such as low yield, low molecular weight and polydispersity of HA obtained from these cultures. Optimisation of bioprocess parameters and downstream purification parameters are being addressed to overcome these challenges. We explore these problems from the perspective of microbial heterogeneity, since variations in phenotype affect the yield and properties of the product in a bioreactor. For this perspective, a method to quantitatively assess the occurrence of heterogenous phenotypes depending on the amount of HA produced at the single-cell level is required. Here, we evaluated for the first time the use of calcofluor white staining method combined with in vivo fluorescence confocal microscopy to quantify the heterogeneity in phenotypes of L. lactis cells engineered for HA production. From the microscopy image analysis, we found that the population harbours significant heterogeneity with respect to HA production and our novel approach successfully differentiates these phenotypes. Using the fluorescence intensity levels, first we were able to confidently differentiate cells not expressing HA (Host cells without HA genes for expression) from cells with genes for HA production (GJP2) and induced for expression, as there is a consistently two-fold higher level of expression in the GJP2 cells independently of the cell size. Further, this method revealed the occurrence of two different phenotypes in GJP2 cultures, one of a high-expression phenotype (40% of the population) and the other one of a low-expression (remaining 60% of the population), and it is the high expression phenotype that contributes to the increase in the HA expression of the GJP2 population compared with the host cells. Thus, it is essential to identify the extrinsic and intrinsic factors that can favour most of the cells in the population to switch and stabilise into the high-expression phenotype state in a bioreactor, for higher yield and possibly reduced heterogeneity of the product, such as polydispersity in chain lengths. For such optimisation studies, this in vivo method serves as a promising tool for rapid detection of phenotypes in the bioreactor samples under varying conditions, allowing fine tuning of the factors to stabilise high-expression phenotypes thereby maximizing the yield. Graphical Abstractdone. Key PointsO_LICalcofluor staining successfully differentiated the phenotypes based on HA levels. C_LIO_LIThis study revealed the occurrence of significant heterogeneity in HA expression. C_LIO_LIThis method will aid for rapid optimization of factors for improved HA production. C_LI

bioengineering↗

bioRxiv2020

Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity: Mount Sinai DToxS LINCS Center Dataset

The Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is one of the centers of the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. A key aim of DToxS is to generate both proteomic and transcriptomic signatures that can predict adverse effects, especially cardiotoxicity, of kinase inhibitors approved by the Food and Drug Administration. Towards this goal, high throughput shot-gun proteomics experiments (317 cell line/drug combinations + 64 control lysates) have been conducted at the Center for Advanced Proteomics Research at Rutgers University - New Jersey Medical School. Using computational network analyses, these proteomic data can be integrated with transcriptomic signatures generated in tandem to identify cellular signatures of cardiotoxicity that may predict kinase inhibitor-induced toxicity and possible mitigation. Both raw and processed proteomics data have been carefully screened for quality and made publicly available via the PRIDE database. As such, this broad protein kinase inhibitor-stimulated cardiomyocyte proteomic data and signature set is valuable for the prediction of drug toxicities. Links to: Metadata Tables O_TBL View this table: org.highwire.dtl.DTLVardef@1cda9f8org.highwire.dtl.DTLVardef@1520e05org.highwire.dtl.DTLVardef@16a35borg.highwire.dtl.DTLVardef@3ee6e7org.highwire.dtl.DTLVardef@1a98664_HPS_FORMAT_FIGEXP M_TBL C_TBL

pharmacology and toxicology↗

bioRxiv2019

ChassiDex: A microbial database useful for synthetic biology applications

ChassiDex is an open-source, non-profit online host organism database that houses a repository of molecular, biological and genetic data for model organisms with applications in synthetic biology. The structured user-friendly environment makes it easy to browse information. The database consists of a page for each model organism subdivided into sections such as Growth Characteristics, Strain diversity, Culture sources, Maintenance protocol, Transformation protocol, BioBrick parts and commonly used vectors. With tools such as CUTE built for codon usage table generator, it is also easy to generate and download accurate novel codon tables for unconventional hosts in suitable formats. This database was built as a project for the International Genetically Engineered Machine Competition in 2017 with the mission of making it easy to shift from working with one host organism to another unconventional host organism for any researcher in the field of synthetic biology. The code along with other instructions for the usage of the database and tools are publicly available at the GitHub page. We encourage the synthetic biology community to contribute to the database by adding data for any additional or existing host organism.\n\nhttps://chassidex.org; https://github.com/ChassiDex

synthetic biology↗

bioRxiv2018

Systems therapeutics analyses identify genomic signatures defining responsiveness to allopurinol and combination therapy for lung cancer

The ability to predict responsiveness to drugs in individual patients is limited. We hypothesized that integrating molecular information from databases would yield predictions that could be experimentally tested to develop genomic signatures for sensitivity or resistance to specific drugs. We analyzed TCGA data for lung adenocarcinoma (LUAD) patients and identified a subset where xanthine dehydrogenase expression correlated with decreased survival. We tested allopurinol, a FDA approved drug that inhibits xanthine dehydrogenase on a library of human Non Small Cell Lung Cancer (NSCLC) cell lines from CCLE and identified sensitive and resistant cell lines. We utilized the gene expression profiles of these cell lines to identify six-gene signatures for allopurinol sensitive and resistant cell lines. Network building and analyses identified JAK2 as an additional target in allopurinol-resistant lines. Treatment of resistant cell lines with allopurinol and CEP-33779 (a JAK2 inhibitor) resulted in cell death. The effectiveness of allopurinol alone or allopurinol and CEP-33779 were verified in vivo using tumor formation in NCR-nude mice. We utilized the six-gene signatures to predict five additional allopurinolsensitive NSCLC lines, and four allopurinol-resistant lines susceptible to combination therapy. We found that drug treatment of all cell lines yielded responses as predicted by the genomic signatures. We searched the library of patient derived NSCLC tumors from Jackson Laboratory to identify tumors that would be predicted to be sensitive or resistant to allopurinol treatment. Both patient derived tumors predicted to be allopurinol sensitive showed the predicted sensitivity, and the predicted resistant tumors were sensitive to combination therapy. These data indicate that we can use integrated molecular information from cancer databases to predict drug responsiveness in individual patients and thus enable precision medicine.

systems biology↗

bioRxiv2018

Uncovering novel pathways for enhancing hyaluronan synthesis in recombinant Lactococcus lactis: Genome-scale metabolic modelling and experimental validation

Hyaluronan (HA) is a naturally occurring high-value polysaccharide with important medical applications. HA is commercially produced from pathogenic microbial sources. HA-producing recombinant cell factories that are being developed with GRAS organisms are comparatively less productive than the best natural producers. The metabolism of these recombinant systems needs to be more strategically engineered to achieve significant improvement. Here, we use a genome-scale metabolic network model to account for the entire metabolic network of the cell to predict strategies for improving HA production. We here analyze the metabolic network of Lactococcus lactis adapted to produce HA, and identify non-conventional overexpression and knock-out strategies to enhance HA flux.\n\nTo experimentally validate our predictions, we identify an alternate route for enhancement of HA synthesis, originating from the nucleoside inosine, which has the capacity to function in parallel with the traditionally known route from glucose. Adopting this strategy resulted in a 2.8-fold increase in HA yield. The strategies identified and the experimental results show that the cell is capable of involving a larger subset of metabolic pathways in HA production. Apart from being the first report of the use of a nucleoside to improve HA production, our study shows how experimental results enable model refinement. Overall, we point out that well-constructed genome-scale metabolic models could be very potent tools to derive efficient strategies to improve biosynthesis of important high-value products.

bioengineering↗

bioRxiv2017

A Comparison of mRNA Sequencing with Random Primed and 3’-Directed Libraries

Deep mRNA sequencing (mRNAseq) is the state-of-the-art for whole transcriptome measurements. A key step is creating a library of cDNA sequencing fragments from RNA. This is generally done by random priming, creating multiple sequencing fragments along the length of each transcript. A 3 end-focused library approach cannot detect differential splicing, but has potentially higher throughput at lower cost (~10-fold lower), along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) to correct for PCR bias. Here, we compare implementation of such a 3-digital gene expression (3-DGE) approach with \"conventional\" random primed mRNAseq, which has not yet been done. We find that while conventional mRNAseq detects ~15% more genes, the resulting lists of differentially expressed genes and therefore biological conclusions and gene signatures are highly concordant between the two techniques. We also find good quantitative agreement on the level of individual genes between the two techniques in terms of both read counts and fold change between two conditions. We conclude that for high-throughput applications, the potential cost savings associated with the 3-DGE approach are a very reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable much larger scale studies focused on not only differential expression analysis, but also quantitative transcriptome profiling. The computational scripts and programs, along with experimental standard operating procedures used in our pipeline presented here, are freely available on our website (www.dtoxs.org).

genomics↗