Biology subjects

Singh, R.

Publications and source records attributed to Singh, R..

At least 235 records · Page 13Linked to original sources

bioRxiv2021

Inhibitors of the Small Membrane (M) Protein Viroporin Prevent Zika Virus Infection

Flaviviruses, including Zika virus (ZIKV), are a significant global health concern, yet no licensed antivirals exist to treat disease. The small Membrane (M) protein plays well-defined roles during viral egress and remains within virion membranes following release and maturation. However, it is unclear whether M plays a functional role in this setting. Here, we show that M forms oligomeric membrane-permeabilising channels in vitro, with increased activity at acidic pH and sensitivity to the prototypic channel-blocker, rimantadine. Accordingly, rimantadine blocked an early stage of ZIKV cell culture infection. Structure-based channel models, comprising hexameric arrangements of two trans-membrane domain protomers were shown to comprise more stable assemblages than other oligomers using molecular dynamics (MD) simulations. Models contained a predicted lumenal rimantadine binding site, as well as a second druggable target region on the membrane-exposed periphery. In silico screening enriched for repurposed drugs/compounds predicted to bind to either one site or the other. Hits displayed superior potency in vitro and in cell culture compared with rimantadine, with efficacy demonstrably linked to virion-resident channels. Finally, rimantadine effectively blocked ZIKV viraemia in preclinical models, supporting that M constitutes a physiologically relevant target. This could be explored by repurposing rimantadine, or development of new M-targeted-therapies.

microbiology↗

bioRxiv2021

Comparative evaluation of plasma protein purification and 2-D gel electrophoresis protocols for analysis of HIV-1 infected human plasma proteins

Purification of proteins from human plasma is a herculean task to perform 2-D gel electrophoresis. Human plasma contains nearly 70% albumin and globulin. The removal of such high abundance high molecular weight proteins is very difficult before performing 2-D gel electrophoresis. It becomes more difficult when we intent to investigate in infectious diseases like HIV/AIDS. We tried to the best of our efforts adopting various organic and non-organic based protocols based on various published papers. After failure of these protocols in results of 2-D gel-electrophoresis Aurum serum mini kit (Bio-Rad, USA) was adopted for plasma protein purification for performing 2-D gel electrophoresis. The low-abundance proteins were better resolved by 10% SDS-PAGE in 2-D gel-electrophoresis. Then,we extended the MALDI-TOF/TOF analysis of low-abundance proteins in human plasma by adopting the Aurum serum mini kit (Bio-Rad, USA) for 2-D gel electrophoresis. Thus, we concluded that, depletion of high abundant proteins like albumin and globulin, the use of the Aurum serum mini kit (Bio-Rad, USA) is the protocol of choice to perform the 2-D gel electrophoresis of HIV-1 infected human plasma.

biochemistry↗

bioRxiv2021

Pathogenic bacteria grown in iron and zinc milieu exhibit magnetotaxis

The growing number of multiple drug resistant (MDR) bacteria and the dwindling pipeline of new antibiotics are driving us towards a post-antibiotic era in which even common infections would become difficult to treat. To address this, an antibiotic-free strategy that can combat multiple bacteria is recommended. Most of the proposed approaches nevertheless have several limitations, including bacterial targeting. To overcome such limitations, the proposed strategy employs the bacterial machinery to self-destruct. Herein, the biosynthesis of magnetic nanoparticle (MNP) is reported for the first time in multiple pathogenic bacteria, including MDR bacteria. The intracellular MNPs composed of superparamagnetic zinc ferrites were formed in presence of iron and zinc precursors. Exposure of the treated bacteria/biofilms to an alternating magnetic field (AMF) exhibited hyperthermia (5-6{degrees}C) and a dramatic decrease in bacterial viability, suggesting the MNPs therapeutic potential. Likewise, the bacteria existing in vivo biosynthesize the MNPs by mining these elements from the host. To determine its therapeutic efficacy, the infected tissues were exposed directly to AMF. A 3-4 log reduction in bacterial burden, as compared to antibiotics treatment, confirmed the significance of using naturally existing MNPs to combat bacterial infections. The proposed broad-spectrum approach can therefore aid in overcoming the challenges facing anti-bacterial therapies.

microbiology↗

bioRxiv2021

Discovery of a first-in-class inhibitor of the PRMT5-substrate adaptor interaction

PRMT5 and its substrate adaptor proteins (SAPs), pICln and Riok1, are synthetic lethal dependencies in MTAP-deleted cancer cells. SAPs share a conserved PRMT5 binding motif (PBM) which mediates binding to a surface of PRMT5 distal to the catalytic site. This interaction is required for methylation of several PRMT5 substrates, including histone and spliceosome complexes. We screened for small molecule inhibitors of the PRMT5-PBM interaction and validated a compound series which binds to the PRMT5-PBM interface and directly inhibits binding of SAPs. Mode of action and structure determination studies revealed that these compounds form a covalent bond between a halogenated pyridazinone group and cysteine 278 of PRMT5. Optimization of the starting hit produced a lead compound, BRD0639, which engages the target in cells, disrupts the PRMT5-RIOK1 complex, and reduces substrate methylation. BRD0639 is a first-in-class PBM-competitive small molecule that can support studies of PBM-dependent PRMT5 activities and the development of novel PRMT5 inhibitors that selectively target these functions.

cancer biology↗

bioRxiv2021

MDA5 autoimmune disease variant M854K prevents ATP-dependent structural discrimination of viral and cellular RNA

Our innate immune responses to viral RNA are vital defenses. Long cytosolic double-stranded RNA (dsRNA) is recognized by MDA5. The ATPase activity of MDA5 contributes to its dsRNA binding selectivity. Mutations that reduce RNA selectivity can cause autoimmune disease. Here, we show how the disease-associated MDA5 variant M854K perturbs MDA5-dsRNA recognition. M854K MDA5 constitutively activates interferon signaling in the absence of exogenous RNA. M854K MDA5 lacks ATPase activity and binds more tightly to synthetic Alu:Alu dsRNA. CryoEM structures MDA5-dsRNA filaments at different stages of ATP hydrolysis show that the K854 side-chain forms polar bonds that constrain the conformation of MDA5 subdomains, disrupting key steps in the ATPase cycle-RNA footprint expansion and helical twist modulation. The M854K mutation inhibits ATP-dependent RNA proofreading via a novel allosteric mechanism, allowing MDA5 to form signaling complexes on endogenous RNAs. This work provides new insights on how MDA5 recognizes dsRNA in health and disease.

biochemistry↗

bioRxiv2021

microRNA775 targets a β-(1,3)-galactosyltransferase to regulate growth and development in Arabidopsis thaliana

MicroRNAs are critical regulators of gene expression in plants and other organisms, and are involved in regulating plethora of developmental processes. Evolutionarily, miRNAs can be ancient and conserved across species or recently evolved and young, which are not conserved across diverse plant groups. miR775 is a non-conserved miRNA identified only in Arabidopsis thaliana. Here, we investigated the functional significance of miR775 in A. thaliana and observed that miR775 targets a probable {beta}-(1,3)-galactosyltransferase gene at post transcriptional level. Phenotypic analysis of miR775 over-expression lines and the target mutant suggested miR775 regulates rosette size by elongating petiole length and increasing leaf area. Further, the expression of miR775 was found to be up-regulated in response to UV-B and hypoxia. Our results also suggest that miR775 regulated {beta}-(1,3)-galactosyltransferase may involve in regulating the {beta}-(1,3)-galactan content of arabinogalactans. Collectively, our findings establish a role of miR775 in regulating growth and development in A. thaliana. HighlightsO_LIThe role of an uncharacterized microRNA, miR775 has been explored C_LIO_LImiR775 targets a probable {beta}-(1,3)-galactosyltransferase involved in complex carbohydrate biosynthesis C_LIO_LImiR775 regulates rosette size in A. thaliana and may play role under UV light and hypoxia C_LI

plant biology↗

bioRxiv2021

Abolished miR158 activity leads to 21-nucleotide tertiary phasiRNA biogenesis that targets NHX2 in Arabidopsis thaliana

Small RNAs including microRNAs (miRNAs) are short 20-24-nucleotide non-coding RNAs. They are key regulators of gene expression in plants and other organisms. Some small RNAs, mostly 22-nucleotide long trigger biogenesis of secondary small interfering RNAs (siRNAs). Those siRNAs having distinctive phased configuration are known as phased siRNAs (phasiRNAs) and act either in cis or trans enhancing silencing cascade. Here, we report natural variants of MIR158 having deletions or insertions led to negligible or reduced expression of miR158. The deletion/insertion events affected processing of primary transcript of miR158 to precursor and to mature miR158. We show that miR158 targets a pseudo-pentatricopeptide gene and its abolished activity led to 21-nucleotide tertiary phasiRNA generation from its target. The biogenesis of these phasiRNAS is triggered by TAS2 derived two siRNAs. Accordingly, small RNA analyses of these natural variants, mutants and over-expression lines of MIR158 or its target exhibited enhanced or reduced phasiRNA biogenesis. Finally, we functionally validated the highest expressed tertiary phasiRNA that targets NHX2 thereby regulating transpiration and stomatal conductance. Overall, we deciphered a new module of small RNA network, miRNA-TAS-siRNA-pseudogene-tertiary phasiRNA-NHX2, suggesting an additional layer of gene regulation and larger role of pseudogene in plants.

plant biology↗

bioRxiv2021

Sequence-based prediction of protein-protein interactions: a structure-aware interpretable deep learning model

Protein-protein interaction (PPI) networks have proven to be a valuable tool in systems biology to facilitate the discovery and understanding of protein function. Unfortunately, experimental PPI data remains sparse in most model organisms and even more so in other species. Existing methods for computational prediction of PPIs seek to address this limitation, and while they perform well when sufficient within-species training data is available, they generalize poorly to new species or often require specific types and sizes of training data that may not be available in the species of interest. We therefore present D-SCRIPT, a deep learning method for predicting a physical interaction between two proteins given just their sequences. Compared to existing methods, D-SCRIPT generalizes better to new species and is robust to limitations in training data size. Our approach encodes the intuition that for two proteins to physically interact, a subset of amino acids from each protein should be in contact with the other. The intermediate stages of D-SCRIPT directly implement this intuition; the penultimate stage in D-SCRIPT is a rough estimate of the inter-protein contact map of the protein dimer. This structurally-motivated design enables interpretability of our model and, since structure is more conserved evolutionarily than sequence, improves generalizability across species. We show that a D-SCRIPT model trained on 38,345 human PPIs enables significantly improved functional characterization of fly proteins compared to the state-of-the-art approach. Evaluating the same D-SCRIPT model on protein complexes with known 3-D structure, we find that the inter-protein contact map output by D-SCRIPT has significant overlap with the ground truth. Our work suggests that recent advances in deep learning language modeling of protein structure can be leveraged for protein interaction prediction from sequence. D-SCRIPT is available at http://dscript.csail.mit.edu.

bioinformatics↗

bioRxiv2021

A highly thermotolerant, trimeric SARS-CoV-2 receptor binding domain derivative elicits high titers of neutralizing antibodies

The Receptor Binding Domain (RBD) of SARS-CoV-2 is the primary target of neutralizing antibodies. We designed a trimeric, highly thermotolerant glycan engineered RBD by fusion to a heterologous, poorly immunogenic disulfide linked trimerization domain derived from cartilage matrix protein. The protein expressed at a yield of [~]80-100 mg/liter in transiently transfected Expi293 cells, as well as CHO and HEK293 stable cell lines and formed homogeneous disulfide-linked trimers. When lyophilized, these possessed remarkable functional stability to transient thermal stress of upto 100 {degrees}C and were stable to long term storage of over 4 weeks at 37 {degrees}C unlike an alternative RBD-trimer with a different trimerization domain. Two intramuscular immunizations with a human-compatible SWE adjuvanted formulation, elicited antibodies with pseudoviral neutralizing titers in guinea pigs and mice that were 25-250 fold higher than corresponding values in human convalescent sera. Against the beta (B.1.351) variant of concern (VOC), pseudoviral neutralization titers for RBD trimer were [~] three-fold lower than against wildtype B.1 virus. RBD was also displayed on a designed ferritin-like Msdps2 nanoparticle. This showed decreased yield and immunogenicity relative to trimeric RBD. Replicative virus neutralization assays using mouse sera demonstrated that antibodies induced by the trimers neutralized all four VOC to date, namely B.1.1.7, B.1.351, P.1 and B.1.617.2 without significant differences. Trimeric RBD immunized hamsters were protected from viral challenge. The excellent immunogenicity, thermotolerance, and high yield of these immunogens suggest that they are a promising modality to combat COVID-19, including all SARS-CoV-2 VOC to date.

microbiology↗

bioRxiv2020

Adducin Regulates Sarcomere Disassembly During Cardiomyocyte Mitosis

Recent interest in understanding cardiomyocyte cell-cycle has been driven by potential therapeutic applications in cardiomyopathy. However, despite recent advances, cardiomyocyte mitosis remains a poorly understood process. For example, it is unclear how sarcomeres are disassembled during mitosis to allow abscission of daughter cardiomyocytes. Here we identify adducin as a regulator of sarcomere disassembly during mammalian cardiomyocyte mitosis. /{gamma}-adducins are selectively expressed in neonatal mitotic cardiomyocytes, and their levels decline precipitously thereafter. Cardiomyocyte-specific overexpression of various splice isoforms and phosphoforms of -adducin in-vitro and in-vivo identified Thr445/Thr480 phosphorylation of a short isoform of adducin as a potent inducer of neonatal cardiomyocyte sarcomere disassembly. Concomitant overexpression of this -adducin variant along with {gamma}-adducin resulted in stabilization of the adducin complex and persistent sarcomere disassembly in adult mice, which is mediated by interaction with -actinin. These results highlight an important mechanism for coordination of cytoskeletal morphological changes during cardiomyocyte mitosis.

cell biology↗

bioRxiv2020

Standardizing a protocol for studying pH-dependent transient conformations using computer simulations

1.Understanding pH-dependent protein stability is important in biological - transport, storage, and delivery, in vivo conditions such as aggregation potential in neurodegenerative disease, and in studying the folding/unfolding of proteins. Using computer simulations, we can replace complex experimental determination and provide an atomistic-level interpretation of the cause and effect of pH on protein stability. Here, we standardize a method that provides a framework through which we examined pH-dependent transient conformations during unfolding simulations of proteins. Constant pH simulations utilized in the prediction of pKa values of charged groups of the peptide. The calculated pKa values employed to fix the appropriate protonation state of the amino acid to simulate the effect of pH on the system. Trajectories from multiple high-temperature MD simulations of the protein sample the conformational space during unfolding for a given pH state. The ensemble of conformations is analyzed from its free energy landscape to identify transient and stable conformations both at a given pH and between different pH. As a test system RN80, a protein fragment analog of the C-peptide from bovine pancreatic ribonuclease-A used to measure the accuracy of the predictions from simulations. Experimental measures of the helix content determined as a function of pH display a bell-shaped curve, i.e. RN80 alpha-helix formation is maximum at pH5 with a subsequent loss in helicity at higher and lower pH. The main forces stabilizing the alpha-helix are a salt-bridge formed between Glu-2 and Arg-10 and cation-pi-interaction between Tyr-8 and His-12. Our protocol includes constant pH calculations, optimal high-temperature simulations, and Free Energy landscape analysis exhibited the agreement with the experimental observations.

bioinformatics↗

bioRxiv2020

Translational control as a novel regulator of gradient sensing and chemotropism in yeast

The yeast mating pathway regulates haploid cell fusion in response to pheromone signaling via a mitogen-activated protein kinase (MAPK) cascade that controls directional growth (chemotropism). However, the regulators of chemotropic morphogenesis are ill-defined. By using a non-biased genome-wide screen, we identified hundreds of genes that affect mating. An additional screens identified and validated >20 novel positive and negative regulators of pheromone gradient sensing, chemotropism, shmoo development, and mating. Aside from known regulators of exocytosis and endocytosis, genes involved in translational control downstream of the G-protein-regulated pheromone and filamentous growth MAPK pathways were identified. These include the Scp160 RNA-binding protein and the Asc1, Rpl12b, and Rpl19b ribosomal proteins (RPs). Importantly, we demonstrate that pheromone treatment and G (Gpa1) activation stimulate Scp160 binding to (and inhibition of) Asc1, which acts downstream of glucose-activated G (Gpa2) on the filamentous growth pathway. Moreover, we identify both Rpl12b and Rpl19b as RP paralog-specific positive regulators of translation of mating components, including Scp160. Thus, opposing MAPK pathways may converge at the level of translational control to regulate signaling output. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/422562v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@3944e1org.highwire.dtl.DTLVardef@1d9204eorg.highwire.dtl.DTLVardef@1d7e902org.highwire.dtl.DTLVardef@2bfc6_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

Plasma neutralizing antibodies in an infant with interclade HIV-1 superinfection preferentially neutralize superinfecting HIV-1 strains

HIV-1 superinfection is defined as infection by an unrelated second strain of HIV-1 after seroconversion due to primary infecting strain and has been associated with development of breadth in the neutralizing antibody (nAb) response, altered disease progression and efficacy of antiretrovirals; though conflicting observations have also been reported. Superinfection has been reported in HIV-1 infected adults. Recently we observed that multivariant infection in infants was associated with early induction of plasma broadly neutralizing antibodies (bnAbs) targeting diverse autologous viruses, however, there is paucity of information on infants with HIV-1 superinfection. Furthermore, the mechanisms by which superinfection in an infant, after priming by an initial infection, potentiate the evolution of a bnAb response have not been evaluated. Herein, we performed a longitudinal analysis and observed evolution of nAb responses in an antiretroviral naive perinatally HIV-1 infected infant, with interclade superinfection (clade C followed by a unique A1C recombinant). The nAb responses broadened rapidly after superinfection targeted an undefined glycan-dependent epitope on the superinfecting variant, while no enrichment of nAb response against the primary infecting strain occurred. Defining virological features in infants with sequential infection with highly divergent circulating viruses that improve nAb responses will contribute information that could be leveraged for optimization of multicomponent candidate vaccines. ImportanceHIV-1 infected infants develop bnAbs rapidly suggesting factors governing bnAb induction in infants are distinct from adults. HIV-1 superinfection is more common in adults whereas the stringent genetic bottleneck for transmission in infants often leads to infection by a single transmitted/founder HIV-1 strain. Longitudinal studies in infants with HIV-1 superinfection can provide key information on the viral factors that induce a bnAb response towards development of a polyvalent vaccine. Herein, we show that in infant who was sequentially infected with two HIV-1 strains from different clades, antibody responses were primarily generated against the superinfecting, second strain of HIV-1. These antibody responses were dependent on glycans, and targeted an undefined epitope in the C3V4 region of HIV-1 Env. A better understanding of how neutralizing antibody responses develop during natural HIV-1 superinfection in infants will provide information relevant to HIV Env vaccine development and evaluation.

immunology↗

bioRxiv2020

Integrating long-range regulatory interactions to predict gene expression using graph convolutional neural networks

Long-range spatial interactions among genomic regions are critical for regulating gene expression, and their disruption has been associated with a host of diseases. However, when modeling the effects of regulatory factors, most deep learning models either neglect long-range interactions or fail to capture the inherent 3D structure of the underlying genomic organization. To address these limitations, we present GC-MERGE, a Graph Convolutional Model for Epigenetic Regulation of Gene Expression. Using a graph-based framework, the model incorporates important information about long-range interactions via a natural encoding of spatial interactions into the graph representation. It integrates measurements of both the spatial genomic organization and local regulatory factors, specifically histone modifications, to not only predict the expression of a given gene of interest but also quantify the importance of its regulatory factors. We apply GC-MERGE to datasets for three cell lines - GM12878 (lymphoblastoid), K562 (myelogenous leukemia), and HUVEC (human umbilical vein endothelial) - and demonstrate its state-of-the-art predictive performance. Crucially, we show that our model is interpretable in terms of the observed biological regulatory factors, high-lighting both the histone modifications and the interacting genomic regions contributing to a genes predicted expression. We provide model explanations for multiple exemplar genes and validate them with evidence from the literature. Our model presents a novel setup for predicting gene expression by integrating multimodal datasets in a graph convolutional framework. More importantly, it enables interpretation of the biological mechanisms driving the models predictions. Available at: https://github.com/rsinghlab/GC-MERGE.

bioinformatics↗

bioRxiv2020

CentTracker: a trainable, machine learning-based tool for large-scale analyses of C. elegans germline stem cell mitosis

Investigating the complex interactions between stem cells and their native environment requires an efficient means to image them in situ. Caenorhabditis elegans germline stem cells (GSCs) are distinctly accessible for intravital imaging; however, long-term image acquisition and analysis of dividing GSCs can be technically challenging. Here we present a systematic investigation into the technical factors impacting GSC physiology during live imaging and provide an optimized method for monitoring GSC mitosis under minimally disruptive conditions. We describe CentTracker, an automated and generalizable image analysis tool that uses machine learning to pair mitotic centrosomes and which can extract a variety of mitotic parameters rapidly from large-scale datasets. We employ CentTracker to assess a range of mitotic features in GSCs and show that subpopulations with distinct mitotic profiles are unlikely to exist within the stem cell pool. We further find evidence for spatial clustering of GSC mitoses within the germline tissue and for biases in mitotic spindle orientation relative to the germlines distal-proximal axis, and thus the niche. The technical and analytical tools provided herein pave the way for large-scale screening studies of multiple mitotic processes in GSCs dividing in situ, in an intact tissue, in a living animal, under seemingly physiological conditions.

cell biology↗

bioRxiv2020

Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation

Mammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. In differentiated cells, contact decay profiles, which clearly distinguish the active and inactive X chromosomes, reveal loss of the inactive X-specific structure at mitosis followed by a rapid reappearance, suggesting a bookkeeping mechanism. In differentiating embryonic stem cells, changes in contact decay profiles are detected in parallel on both the X chromosomes and autosomes, suggesting profound simultaneous reorganization. The onset of the inactive X-specific structure in single cells is notably delayed relative to that of gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Novel computational approaches to effectively align single-cell gene expression, chromatin accessibility, and 3D chromosome structure reveal that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

genomics↗

bioRxiv2020

Survey, Identification and Evaluation of biodiversity of Seabuckthorn (Hippophae salicifolia) in hills of Uttarakhand

Extensive studies were carried out during 2017-2019 to evaluate the Hippophae salicifolia (Seabuckthorn) biodiversity in Uttarakhand for their physico-chemical/biochemical parameters of ripe fruits like acidity (1.78-3.01 %), pH (2.15-2.87), Vitamin C (271-494mg/100g), Total soluble solids (5.1-9.8) etc. Variation was also observed in fruit color (light yellow, yellow, light yellow orange, orange and orange red), fruit size (length 6.29-8.77mm, width 4.80-7.59mm), Juice (44.23-76.18%), Pomace (8.01-28.30%) and seed (6.8-21.1%). On the basis of above parameters, promising morphotypes were identified and conserved at field gene bank at DIBER field station, Auli (Joshimath) 3142m AMSL.

plant biology↗

bioRxiv2020

Sustainable Production of the Biofuel n-Butanol by Rhodopseudomonas palustris TIE-1

Anthropogenic carbon dioxide (CO2) release in the atmosphere from fossil fuel combustion has inspired scientists to study CO2 to fuel conversion. Oxygenic phototrophs such as cyanobacteria have been used to produce biofuels using CO2. However, oxygen generation during oxygenic photosynthesis affects biofuel production efficiency. To produce n-butanol (biofuel) from CO2, here we introduced an n-butanol biosynthesis pathway into an anoxygenic (non-oxygen evolving) photoautotroph, Rhodopseudomonas palustris TIE-1 (TIE-1). Using different carbon, nitrogen, and electron sources, we achieved n-butanol production in wild-type TIE-1 and mutants lacking electron-consuming (nitrogen-fixing) or acetyl-CoA-consuming (polyhydroxybutyrate and glycogen synthesis) pathways. The mutant lacking the nitrogen-fixing pathway produced highest n-butanol. Coupled with novel hybrid bioelectrochemical platforms, this mutant produced n-butanol using CO2, solar panel-generated electricity, and light, with high electrical energy conversion efficiency. Overall, this approach showcases TIE-1 as an attractive microbial chassis for carbon-neutral n-butanol bioproduction using sustainable, renewable, and abundant resources.

bioengineering↗