Biology subjects

Mukhopadhyay, A.

Publications and source records attributed to Mukhopadhyay, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

Generation of fluorescent HCV pseudoparticles to study early viral entry events- involvement of Rab1a in HCV entry

Understanding the early events in viral biology holds the key to the development of preventives. In this study fluorescent Hepatitis C Virus pseudoparticles have been generated where the envelope glycoprotein has a GFP tag. Using these pseudoparticles entry assays were conducted where the entry of the pseudoparticles was tracked via confocal microscopy. Using this system, fusion of host and viral membranes is predicted to occur within 15 minutes of entry in HCV. Using cells with a knockdown for Rab1a, HCV trafficking was observed to be altered, indicating a role of Rab1a in HCV trafficking. In conclusion, this study reports the generation and use of fluorescent pseudoparticles which may be used to understand the early events of viral entry. This system may be adapted for the study of other enveloped viruses as well. HighlightsO_LIFluorescent HCV pseudoparticles have been created to study early entry events. C_LIO_LIHCV entry tracking via confocal microscopy reveals fusion within 15 minutes. C_LIO_LIRab1a is important for HCV trafficking within the cell. C_LI

microbiology↗

bioRxiv2021

Plasmodium falciparum Kelch13 and its artemisinin-resistant mutants assemble as hexamers in solution: a SAXS data driven shape restoration study.

Artemisinin-resistant mutations in PfKelch13 identified worldwide are mostly confined to its BTB/POZ and KRP domains. To date, only two crystal structures of the BTB/POZ-KRP domains as tight dimers are available, which limits structure-based interpretations of its functionality. Our solution Small-Angle X-ray Scattering (SAXS) data driven shape restoration of larger length of protein brought forth that: i) PfKelch13 forms a stable hexamer in P6 symmetry, ii) interactions of the N-termini drive the hexameric assembly, and iii) the six KRP domains project independently in space, forming a cauldron-like architecture. While artemisinin-sensitive mutant A578S packed like the wild-type, hexameric assemblies of dominant artemisinin-resistant mutant proteins R539T and C580Y displayed detectable differences in spatial positioning of their BTB/POZ-KRP domains. Lastly, mapping of mutations known to enable artemisinin resistance explained that most mutations exist mainly in these domains because they are non-detrimental to assembly of mutant PfKelch13 and yet can alter the flux of downstream events essential for susceptibility to artemisinin.

biochemistry↗

bioRxiv2021

High Throughput Fitness Profiling Reveals Loss Of GacS-GacA Regulation Improves Indigoidine Production In Pseudomonas putida

Pseudomonas putida KT2440 is an emerging industrial microbe amenable for use with renewable carbon streams including aromatics such as para-coumarate (pCA). We examined this microbe under common stirred-tank bioreactor parameters with quantitative fitness assays using a pooled transposon library containing nearly all (4,778) non-essential genes. Assessing differential fitness values by monitoring changes in mutant strain abundance over time identified 31 genes with improved fitness in multiple bioreactor-relevant parameters. Twenty-one genes from this subset were reconstructed, including GacA, a signaling protein, TtgB, an ABC transporter, and PP_0063, a lipid A acyltransferase. Twelve deletion strains with roles in varying cellular functions were evaluated for conversion of pCA, to a heterologous bioproduct, indigoidine. Several mutants, such as the {Delta}gacA strain improved both fitness in a bioreactor and showed an 8-fold improvement in indigoidine production (4.5 g/L, 0.29 g/g pCA, 23% MTY) from pCA as the carbon source.

systems biology↗

bioRxiv2020

Nuclear Morphology Optimized Deep Hybrid Learning (NUMODRIL): A novel architecture for accurate diagnosis/prognosis of Ovarian Cancer

Nuclear morphological features are potent determining factors for clinical diagnostic approaches adopted by pathologists to analyse the malignant potential of cancer cells. Considering the structural alteration of nucleus in cancer cells, various groups have developed machine learning techniques based on variation in nuclear morphometric information like nuclear shape, size, nucleus-cytoplasm ratio and various non-parametric methods like deep learning have also been tested for analysing immunohistochemistry images of tissue samples for diagnosing various cancers. Our aim is to study the morphometric distribution of nuclear lamin proteins as a specific parameter in ovarian cancer tissues. Besides being the principal mechanical component of the nucleus, lamins also present a platform for binding of proteins and chromatin thereby serving a wide range of nuclear functions like maintenance of genome stability, chromatin regulation. Altered expression of lamins in different subtypes of cancer is now evident from data across the world. It has already been elucidated that in ovarian cancer, extent of alteration in nuclear shape and morphology can determine degree of genetic changes and thus can be utilized to predict the outcome of low to high form of serous carcinoma. In this work, we have performed exhaustive imaging of ovarian cancer versus normal tissue and introduced a novel Deep Hybrid Learning approach on the basis of the distribution of lamin proteins. Although developed with ovarian cancer datasets in view, this architecture would be of immense importance in accurate and fast diagnosis and prognosis of all types of cancer associated with lamin induced morphological changes and would perform across small/medium to large datasets with equal efficiency. Significance StatementWe have developed a novel Deep Hybrid Learning approach based on nuclear morphology to classify normal and ovarian cancer tissues with highest possible accuracy and speed. Ovarian cancer cells can be easily distinguished from their enlarged nuclear morphology as is evident from lamin A & B distribution pattern. This is the first report to invoke specific nuclear markers like lamin A & B instead of classical haematoxylin-eosin staining in an effort to build parametric datasets. Our approach has been shown to outperform the existing deep learning techniques in training and validation of datasets over a wide range. Therefore this method could be used as a robust model to predict malignant transformations of benign nuclei and thus be implemented in the diagnosis and prognosis of ovarian cancer in future. Most importantly, this method can be perceived as a generalized approach in the diagnosis for all types of cancer.

cancer biology↗

bioRxiv2020

Identification of key immune regulatory genes in HIV-1Progression

In the last few decades, application of DNA microarray technology has sprung up as a powerful technique for discovering stage specific changes in expression pattern of a disease progression. Human Immunodeficiency Virus (HIV) infection causes Acquired Immunodeficiency Syndrome (AIDS) which is one of the most devastating diseases affecting humankind. Here, we have proposed a framework to examine the difference among microarray gene expression data of uninfected and three different HIV-1 infection stages using module preservation statistics. Initially, we detected differentially expressed genes among all the stages and identified coexpression modules by using topological overlap as a dissimilarity measure. To examine relationship among co-expression modules, we have compiled a module eigenegene network for each sample category which models similarity among all coexpression modules. To further examine the network, we have found clusters in it which are termed as meta-modules. Different module preservation statistics with two composite statistics: "Zsummary" and "MedianRank" are utilized to examine changes in structure of coexpression modules. We have applied our proposed methodology to discover modular changes between uninfected and acute samples, acute and chronic samples, chronic and AIDS samples. We have found several interesting results on preservation characteristics of gene modules across different stages. Some genes are identified to be preserved in a pair of stages while alter their characteristics across other stages. We further validated the obtained results using permutation test and classification techniques. Biological significance of the obtained modules have been examined using gene ontology and pathway based analysis. Additionally, we have detected key immune regulatory hub genes in the associated protein-protein interaction networks (PPINs) of the differentially expressed genes (DEGs) using twelve topological and centrality analysis methods. Moreover, we have analyzed the key immune regulatory genes which interacts with HIV-1 proteins inside the preserved and perturbed meta-modules across different HIV-1 stages and thus likely to act as potential biomarkers in HIV-1 progression.

bioinformatics↗

bioRxiv2020

Evolutionarily Driven Domain Swap Alters Sigma Factor Dependence in Bacterial Signaling System

This report presents multi-genomes and experimental evidence that REC protein family expansion occurs when the emergence of new pathways give rise to functional discordance. Specificity between REC-domain containing response regulators with paired histidine kinases are under negative purifying selection, constrained by the presence of other bacterial two-component systems signaling cascades that share sequence and structural identity. Presuming that the two-component systems can evolve by neutral drift when these constraints are relaxed, how might the REC protein family expand when constraints remain intact? Using an unsupervised machine learning approach to observe the sequence landscape of REC domains across long phylogenetic distances, we find that within-gene-recombination, a subcategory of gene conversion, switched the effector domain, and consequently the regulatory context of a duplicated response regulator from transcriptional regulation by {sigma}54 to {sigma}70. We determined that the recombined response regulator diverged from its parent by positive episodic diversifying selection, giving rise to two new residues. Functional experiments of the parent of recombined response regulators in our model system, Pseudomonas putida KT2440, revealed that the parent and recombined response regulators sense and respond to carboxylic acids and that the two new residues in the recombined regulator form a new interaction interface and prevent crosstalk. Overall, our study finds genetic perturbations can create conditions of functional discordance, whereby the REC protein family can evolve by positive diversifying selection.

evolutionary biology↗

bioRxiv2020

Discovering Key Transcriptomic Regulators in Pancreatic Ductal Adenocarcinoma using Dirichlet Process Gaussian Mixture Model

Pancreatic Ductal Adenocarcinoma (PDAC) is the most lethal type of pancreatic cancer (PC), late detection of which leads to its therapeutic failure. This study aims to find out key regulatory genes and their impact on the progression of the disease helping the etiology of the disease which is still largely unknown. We leverage the landmark advantages of time-series gene expression data of this disease, and thereby the identified key regulators capture the characteristics of gene activity patterns in the progression of the cancer. We have identified the key modules and predicted gene functions of top genes from the compiled gene association network (GAN). Here, we have used the natural cubic spline regression model (splineTimeR) to identify differentially expressed genes (DEG) from the PDAC microarray time-series data downloaded from gene expression omnibus (GEO). First, we have identified key transcriptomic regulators (TR) and DNA binding transcription factors (DbTF). Subsequently, the Dirichlet process and Gaussian process (DPGP) mixture model is utilized to identify the key gene modules. A variation of the partial correlation method is utilized to analyze GAN, which is followed by a process of gene function prediction from the network. Finally, a panel of key genes related to PDAC is highlighted from each of the analyses performed. Please note: Abbreviations should be introduced at the first mention in the main text - no abbreviations lists. Suggested structure of main text (not enforced) is provided below.

bioinformatics↗

bioRxiv2020

Optimal inaccuracy: estimating male fitness in the movement-assisted dichogamous species Clerodendrum infortunatum

In hermaphroditic species, sexual interference can drive the evolution of dichogamy, where sporophylls (reproductive parts) are separated in time. However, the separation of sporophylls can lead to pollination inaccuracy, especially in movement-assisted dichogamy, where sporophylls alter their position over time. Is pollination inaccuracy minimised by the second sporophyll taking the exact position of the first? Are the sporophylls optimally positioned and stable in their respective active phases? We address these questions in Clerodendrum infortunatum, a protandrous, movement-assisted dichogamous species. We made predictions from optimality arguments, and tested these by measuring sporophyll angles over time, by experimentally manipulating flowers, and by estimating correlates of the resultant fitness, taking into account pollen export, pollination inaccuracy and the resultant total pollen delivered. Contrary to expectation, anthers do not have a fixed position in the male phase, and pollination inaccuracy is high. Further, when pollen load is highest, anthers are paradoxically not positioned at the pollen export peak. Also, pollen export and pollination accuracy peaks do not align. This seeming maladaptiveness of anther positioning nevertheless results in highest overall male fitness, measured as the total pollen delivered over the entire male phase. Instead of a simple positional exchange of sporophylls, stamens display a more complicated dynamic strategy which appears close to optimal even though naive measures of pollination inaccuracy are high. Such a strategy of maximising overall male fitness, integrating over the dynamics of stamen trajectory, could well be a general characteristic of protandrous movement-assisted dichogamy.

evolutionary biology↗

bioRxiv2020

Ecogenomics of groundwater viruses suggests niche differentiation linked to specific environmental tolerance

Viruses are ubiquitous microbiome components, shaping ecosystems via strain-specific predation, horizontal gene transfer and redistribution of nutrients through host lysis. Viral impacts are important in groundwater ecosystems, where microbes drive many nutrient fluxes and metabolic processes, however little is known about the diversity of viruses in these environments. We analyzed four groundwater plasmidomes and identified 200 viral sequences, which clustered into 41 ~ genus-level viral clusters (equivalent to viral genera) including 9 known and 32 putative new genera. We use publicly available bacterial whole genome sequences (WGS) and WGS from 261 bacterial isolates from this groundwater environment to identify potential viral hosts. We linked 76 of the 200 viral sequences to a range of bacterial phyla, the majority associated with Proteobacteria, followed by Firmicutes, Bacteroidetes and Actinobacteria. The publicly available microbial genome sequences enabled mapping bacterial hosts to a breadth of viral sequences. The WGS of groundwater isolates increased depth of host prediction by allowing identification of hosts at the strain level. The latter included 4 viruses that were almost entirely (>99% query coverage, >99% identity) identified as integrated in the genomes of specific Pseudomonas, Acidovorax and Castellaniella strains, resulting in very high-confidence host assignments. Lastly, 21 of these viruses encoded putative auxiliary metabolite genes for metal and antibiotic resistance, which might drive their infection cycles and/or provide selective advantage to infected hosts. Exploring the groundwater virome provides a necessary foundation for integration of viruses into ecosystem models where they act as key players in microbial adaption to environmental stress. ImportanceTo our knowledge, this is the first study to identify the bacteriophage distribution in a groundwater ecosystem shedding light on their prevalence and distribution across metal-contaminated and background sites. Our study is uniquely based on selective sequencing of solely the extrachromosomal elements of a microbiome followed by analysis for viral signatures, thus establishing a more focused approach for phage identifications. Using this method, we detect several novel phage genera along with those previously established. Our approach of using the whole genome sequences of hundreds of bacterial isolates from the same site enabled us to make host assignments with high confidence, several at strain levels. Certain phage-encoded genes suggest they provide an environment-specific selective advantage to their bacterial hosts. Our study lays the foundation for future research on directed phage isolations using specific bacterial host strains to further characterize groundwater phages, their lifecycles, and its effects on groundwater microbiome and biogeochemistry.

microbiology↗

bioRxiv2020

Functional analysis of the fatty acid and alcohol metabolism of Pseudomonas putida using RB-TnSeq

ABSTRACTWith its ability to catabolize a wide variety of carbon sources and a growing engineering toolkit, Pseudomonas putida KT2440 is emerging as an important chassis organism for metabolic engineering. Despite advances in our understanding of this organism, many gaps remain in our knowledge of the genetic basis of its metabolic capabilities. These gaps are particularly noticeable in our understanding of both fatty acid and alcohol catabolism, where many paralogs putatively coding for similar enzymes co-exist making biochemical assignment via sequence homology difficult. To rapidly assign function to the enzymes responsible for these metabolisms, we leveraged Random Barcode Transposon Sequencing (RB-TnSeq). Global fitness analyses of transposon libraries grown on 13 fatty acids and 10 alcohols produced strong phenotypes for hundreds of genes. Fitness data from mutant pools grown on varying chain length fatty acids indicated specific enzyme substrate preferences, and enabled us to hypothesize that DUF1302/DUF1329 family proteins potentially function as esterases. From the data we also postulate catabolic routes for the two biogasoline molecules isoprenol and isopentanol, which are catabolized via leucine metabolism after initial oxidation and activation with CoA. Because fatty acids and alcohols may serve as both feedstocks or final products of metabolic engineering efforts, the fitness data presented here will help guide future genomic modifications towards higher titers, rates, and yields.IMPORTANCE To engineer novel metabolic pathways into P. putida, a comprehensive understanding of the genetic basis of its versatile metabolism is essential. Here we provide functional evidence for the putative roles of hundreds of genes involved in the fatty acid and alcohol metabolism of this bacterium. These data provide a framework facilitating precise genetic changes to prevent product degradation and channel the flux of specific pathway intermediates as desired.Competing Interest StatementJ.D.K. has financial interests in Amyris, Lygos, Demetrix, Napigen, Maple Bio, and Apertor Labs. C.B.E has a financial interest in Perlumi Chemicals.View Full Text

microbiology↗

bioRxiv2020

Selective Nanotherapeutic Targeting of the Neutrophil Subset Mediating Inflammatory Injury

Inflammatory tissue injury such as acute lung injury (ALI) is a disorder that leads to respiratory failure, a major cause of morbidity and mortality worldwide. Excessive neutrophil influx is a critical pathogenic factor in the development of ALI. Here, we identify the subset of neutrophils that is responsible for ALI and lethality in polymicrobial sepsis. The pro-inflammatory neutrophil subpopulation was characterized by its unique ability to endocytose albumin nanoparticles (ANP), upregulation of pro-inflammatory cytokines and chemokines as well as the excessive production of reactive oxygen species (ROS) in models of endotoxemia and septicemia. ANP delivery of the drug piceatannol, a spleen tyrosine kinase (Syk) inhibitor, to the susceptible subset of neutrophils, prevented ALI and mortality in mice subjected to polymicrobial infection. Targeted inhibition of Syk in ANP-susceptible neutrophils had no detrimental effect on neutrophil-dependent host defense because the subset of ANPlow neutrophils effectively controlled polymicrobial infection. The results show that neutrophil heterogeneity can be leveraged therapeutically to prevent ALI without compromising host defense.Competing Interest StatementABM, AS, KB have interests in the biotechnology company Nano Biotherapeutics Inc.View Full Text

immunology↗

bioRxiv2020

Iron Supplementation Eliminates Antagonistic Interactions Between Root Associated Bacteria

The rhizosphere microbiome (rhizobiome) plays a critical role in plant health and development. However the processes by which the constituent microbes interact to form and maintain a community are not well understood. To investigate these molecular processes, we examined pairwise interactions between 11 different microbial isolates under selected nutrient-rich and nutrient-limited conditions. We observed that when grown with media supplemented with 56 mM glucose, 2 microbial isolates were able to inhibit the growth of 6 out of 11 other microbes tested. The interaction between microbes persisted even after the antagonistic microbe was removed, upon exposure to spent media. To probe the genetic basis for these antagonistic interactions, we used a barcoded transposon library in a proxy bacterium, Pseudomonas putida, to identify genes which showed enhanced sensitivity to the antagonistic factor(s) secreted by Acinetobacter sp. 02. Iron metabolism-related gene clusters in P. putida were implicated by this systems-level analysis. The supplementation of iron prevented the antagonistic interaction in the original microbial pair supporting the hypothesis that iron limitation drives antagonistic microbial interactions between rhizobionts. We conclude that rhizobiome community composition is influenced by competition for limiting nutrients with implications for growth and development of the plant.

microbiology↗

bioRxiv2020

Fine-tuned spatiotemporal dynamics of sporophylls in movement-assisted dichogamy: a study on Clerodendrum infortunatum

Over 70% of flowering plants are hermaphroditic, with male and female parts in the same flower. Hermaphroditism is cost-effective because a common investment in reward and attractive structures yields benefits through both male and female reproductive success. However, the advantage is accompanied by an increased risk of self-pollen deposition, which is disadvantageous for both self-compatible and self-incompatible species. Hermaphroditic plants reduce self-pollen deposition by separating sporophylls (male and female reproductive parts) either spatially (herkogamy) or temporally (dichogamy). In movement-assisted dichogamy, both sporophylls are involved in a coordinated motion, where they move in opposite directions. However, the effectiveness of this adaptation in reducing self-pollen deposition may be compromised at the point when the sporophylls cross each other and are close enough to interfere, resulting in a transition phase problem. The solution to this problem lies in the details of the spatiotemporal dynamics of the sporophylls in relation to their reproductive maturity. We studied these details across the floral lifetime of a protandrous shrub Clerodendrum infortunatum (Lamiaceae), in rainforest fragments of the Western Ghats, India. We took photos of flowers at regular time intervals and measured sporophyll angles from the images. We also carried out a field experiment to determine stigma receptivity. The findings suggest that the effectiveness of dichogamy is maximised through two properties of the transition phase: physical resistance to self-pollen deposition by narrow stigma lobe opening, and chemical non-receptivity of the stigma during this phase. This study emphasises the importance of accessory adaptations in movement-assisted dichogamy to tackle the transition phase problem, which is inherent in this particular form of dichogamy.

plant biology↗

bioRxiv2020

Population dynamics analysis of Saccharomyces cerevisiae deletion library during fed-batch cultivation using Bar-seq

To understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance, we employed a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime. Our results demonstrate the utility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions. We find that mutant population diversity is maintained through multiple seed trains, enabling for large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant external stresses, such as the accumulation of the fermentative byproduct ethanol. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.

microbiology↗

bioRxiv2020

Genome-scale metabolic rewiring to achieve predictable titers rates and yield of a non-native product at scale

Achieving high titer rates and yields (TRY) remains a bottleneck in the production of heterologous products through microbial systems, requiring elaborate engineering and many iterations. Reliable scaling of engineered strains is also rarely addressed in the first designs of the engineered strains. Both high TRY and scale are challenging metrics to achieve due to the inherent trade-off between cellular use of carbon towards growth vs. target metabolite production. We hypothesized that being able to strongly couple product formation with growth may lead to improvements across both metrics. In this study, we use elementary mode analysis to predict metabolic reactions that could be targeted to couple the production of indigoidine, a sustainable pigment, with the growth of the chosen host, Pseudomonas putida KT2440. We then filtered the set of 16 predicted reactions using -omics data. We implemented a total of 14 gene knockdowns using a CRISPRi method optimized for P. putida and show that the resulting engineered P. putida strain could achieve high TRY. The engineered pairing of product formation with carbon use also shifted production from stationary to exponential phase and the high TRY phenotype was maintained across scale. In one design cycle, we constructed an engineered P. putida strain that demonstrates close to 50% maximum theoretical yield (0.33 g indigoidine/g glucose consumed), reaching 25.6 g/L indigoidine and a rate of 0.22g/l/h in exponential phase. These desirable phenotypes were maintained from batch to fed-batch cultivation mode, and from 100ml shake flasks to 250 mL ambr(R) and 2 L bioreactors.

bioengineering↗

bioRxiv2019

Chemoinformatic-guided engineering of polyketide synthases

Polyketide synthase (PKS) engineering is an attractive method to generate new molecules such as commodity, fine and specialty chemicals. A significant challenge in PKS design is engineering a partially reductive module to produce a saturated {beta}-carbon through a reductive loop exchange. In this work, we sought to establish that chemoinformatics, a field traditionally used in drug discovery, could provide a viable strategy to reductive loop exchanges. We first introduced a set of donor reductive loops of diverse genetic origin and chemical substrate structures into the first extension module of the lipomycin PKS (LipPKS1). Product titers of these engineered unimodular PKSs correlated with atom pair chemical similarity between the substrate of the donor reductive loops and recipient LipPKS1, reaching a titer of 165 mg/L of short chain fatty acids produced by Streptomyces albus J1074 harboring these engineered PKSs. Expanding this method to larger intermediates requiring bimodular communication, we introduced reductive loops of divergent chemosimilarity into LipPKS2 and determined triketide lactone production. Collectively, we observed a statistically significant correlation between atom pair chemosimilarity and production, establishing a new chemoinformatic method that may aid in the engineering of PKSs to produce desired, unnatural products.

biochemistry↗

bioRxiv2019

Native plasmid-encoded mercury resistance genes are functional and demonstrate natural transformation in environmental bacterial isolates

Plasmid-mediated horizontal gene transfer (HGT) is a major driver of genetic diversity in bacteria. We experimentally validated the function of a putative mercury resistance operon present on an abundant 8 kilobase pair native plasmid found in groundwater samples without detectable levels of mercury. Phylogenetic analyses of the plasmid-encoded mercury reductases from the studied groundwater site show them to be distinct from those reported in proximal metal-contaminated sites. We synthesized the entire native plasmid and demonstrated that the plasmid was sufficient to confer functional mercury resistance in Escherichia coli. Given the possibility that natural transformation is a prevalent HGT mechanism in the low cell density environments of groundwaters, we also assayed bacterial strains from this environment for competence. We used the native plasmid-encoded metal resistance to design a screen and identified 17 strains positive for natural transformation. We selected 2 of the positive strains along with a model bacterium to fully confirm HGT via natural transformation. From an ecological perspective, the role of the native plasmid population in providing advantageous traits combined with the microbiomes capacity to take up environmental DNA enables rapid adaptation to environmental stresses.\n\nImportanceHorizontal transfer of mobile genetic elements via natural transformation has been poorly understood in environmental microbes. Here, we confirm the functionality of a native plasmid-encoded mercury resistance operon in a model microbe and then query for the dissemination of this resistance trait via natural transformation into environmental bacterial isolates. We identify seventeen strains including Gram-positive and Gram-negative bacteria to be naturally competent. These strains were able to successfully take up the plasmid DNA and obtain a clear growth advantage in the presence of mercury. Our study provides important insights into gene dissemination via natural transformation enabling rapid adaptation to dynamic stresses in groundwater environments.

molecular biology↗

bioRxiv2019

Identification, characterization, and application of a highly sensitive lactam biosensor from Pseudomonas putida

Caprolactam is an important polymer precursor to nylon traditionally derived from petroleum and produced on a scale of 5 million tons per year. Current biological pathways for the production of caprolactam are inefficient with titers not exceeding 2 mg/L, necessitating novel pathways for its production. As development of novel metabolic routes often require thousands of designs and result in low product titers, a highly sensitive biosensor for the final product has the potential to rapidly speed up development times. Here we report a highly sensitive biosensor for valerolactam and caprolactam from Pseudomonas putida KT2440 which is >1000x more sensitive to exogenous ligand than previously reported sensors. Manipulating the expression of the sensor oplR (PP_3516) substantially altered the sensing parameters, with various vectors showing Kd values ranging from 700 nM (79.1 g/L) to 1.2 mM (135.6 mg/L). Our most sensitive construct was able to detect in vivo production of caprolactam above background at ~6 g/L. The high sensitivity and range of OplR is a powerful tool towards the development of novel routes to the biological synthesis of caprolactam. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/700484v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@ff5b8corg.highwire.dtl.DTLVardef@d365aaorg.highwire.dtl.DTLVardef@b79b18org.highwire.dtl.DTLVardef@27732f_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗