PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics.

PERCEPTRON is a next-generation freely available web-based proteoform identification and characterization platform for top-down proteomics (TDP). PERCEPTRON search pipeline brings together algorithms for (i) intact protein mass tuning, (ii) de novo sequence tags-based filtering, (iii) characterization of terminal as well as post-translational modifications, (iv) identification of truncated proteoforms, (v) in silico spectral comparison, and (vi) weight-based candidate protein scoring. High-throughput performance is achieved through the execution of optimized code via multiple threads in parallel, on graphics processing units (GPUs) using NVidia Compute Unified Device Architecture (CUDA) framework. An intuitive graphical web interface allows for setting up of search parameters as well as for visualization of results. The accuracy and performance of the tool have been validated on several TDP datasets and against available TDP software. Specifically, results obtained from searching two published TDP datasets demonstrate that PERCEPTRON outperforms all other tools by up to 135% in terms of reported proteins and 10-fold in terms of runtime. In conclusion, the proposed tool significantly enhances the state-of-the-art in TDP search software and is publicly available at https://perceptron.lums.edu.pk. Users can also create in-house deployments of the tool by building code available on the GitHub repository (http://github.com/BIRL/Perceptron).

The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS.

The Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.

Evolution of efficacious pangenotypic hepatitis C virus therapies.

Hepatitis C compromises the quality of life of more than 350 million individuals worldwide. Over the last decade, therapeutic regimens for treating hepatitis C virus (HCV) infections have undergone rapid advancements. Initially, structure-based drug design was used to develop molecules that inhibit viral enzymes. Subsequently, establishment of cell-based replicon systems enabled investigations into various stages of HCV life cycle including its entry, replication, translation, and assembly, as well as role of host proteins. Collectively, these approaches have facilitated identification of important molecules that are deemed essential for HCV life cycle. The expanded set of putative virus and host-encoded targets has brought us one step closer to developing robust strategies for efficacious, pangenotypic, and well-tolerated medicines against HCV. Herein, we provide an overview of the development of various classes of virus and host-directed therapies that are currently in use along with others that are undergoing clinical evaluation.

CRISPR-Cas13a mediated targeting of hepatitis C virus internal-ribosomal entry site (IRES) as an effective antiviral strategy.

Hepatitis C is an inflammatory liver disease caused by the single-stranded RNA (ssRNA) hepatitis C virus (HCV). The genetic diversity of the virus and quasispecies produced during replication have resulted in viral resistance to direct-acting antivirals (DAAs) as well as impediments in vaccine development. The recent adaptation of CRISPR-Cas as an alternative antiviral approach has demonstrated degradation of viral nucleic acids in eukaryotes. In particular, the CRISPR-effector Cas13 enzyme has been shown to target ssRNA viruses effectively. In this work, we have employed Cas13a to knockdown HCV in mammalian cells. Using a computational screen, we identified several potential Cas13a target sites within highly conserved regions of the HCV internal ribosomal entry site (IRES). Our results demonstrate significant inhibition of HCV replication as well as translation in huh-7.5 cells with minimal effects on cell viability. These findings were validated using a multi-modality approach involving qRT-PCR, luciferase assay, and MTT cell viability assay. In conclusion, the CRISPR-Cas13a system efficiently targets HCV in vitro, suggesting its potential as a programmable therapeutic antiviral strategy.

A cyanobacterial photorespiratory bypass model to enhance photosynthesis by rerouting photorespiratory pathway in C3 plants.

Plants employ photosynthesis to produce sugars for supporting their growth. During photosynthesis, an enzyme Ribulose 1,5 bisphosphate carboxylase/oxygenase (Rubisco) combines its substrate Ribulose 1,5 bisphosphate (RuBP) with CO2 to produce phosphoglycerate (PGA). Alongside, Rubisco also takes up O2 and produce 2-phosphoglycolate (2-PG), a toxic compound broken down into PGA through photorespiration. Photorespiration is not only a resource-demanding process but also results in CO2 loss which affects photosynthetic efficiency in C3 plants. Here, we propose to circumvent photorespiration by adopting the cyanobacterial glycolate decarboxylation pathway into C3 plants. For that, we have integrated the cyanobacterial glycolate decarboxylation pathway into a kinetic model of C3 photosynthetic pathway to evaluate its impact on photosynthesis and photorespiration. Our results show that the cyanobacterial glycolate decarboxylation bypass model exhibits a 10% increase in net photosynthetic rate (A) in comparison with C3 model. Moreover, an increased supply of intercellular CO2 (Ci) from the bypass resulted in a 54.8% increase in PGA while reducing photorespiratory intermediates including glycolate (- 49%) and serine (- 32%). The bypass model, at default conditions, also elucidated a decline in phosphate-based metabolites including RuBP (- 61.3%). The C3 model at elevated level of inorganic phosphate (Pi), exhibited a significant change in RuBP (+ 355%) and PGA (- 98%) which is attributable to the low availability of Ci. Whereas, at elevated Pi, the bypass model exhibited an increase of 73.1% and 33.9% in PGA and RuBP, respectively. Therefore, we deduce a synergistic effect of elevation in CO2 and Pi pool on photosynthesis. We also evaluated the integrative action of CO2, Pi, and Rubisco carboxylation activity (Vcmax) on A and observed that their simultaneous increase raised A by 26%, in the bypass model. Taken together, the study potentiates engineering of cyanobacterial decarboxylation pathway in C3 plants to bypass photorespiration thereby increasing the overall efficiency of photosynthesis.

SPECTRUM - A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data.

Top-Down Proteomics (TDP) is an emerging proteomics protocol that involves identification, characterization, and quantitation of intact proteins using high-resolution mass spectrometry. TDP has an edge over other proteomics protocols in that it allows for: (i) accurate measurement of intact protein mass, (ii) high sequence coverage, and (iii) enhanced identification of post-translational modifications (PTMs). However, the complexity of TDP spectra poses a significant impediment to protein search and PTM characterization. Furthermore, limited software support is currently available in the form of search algorithms and pipelines. To address this need, we propose 'SPECTRUM', an open-architecture and open-source toolbox for TDP data analysis. Its salient features include: (i) MS2-based intact protein mass tuning, (ii) de novo peptide sequence tag analysis, (iii) propensity-driven PTM characterization, (iv) blind PTM search, (v) spectral comparison, (vi) identification of truncated proteins, (vii) multifactorial coefficient-weighted scoring, and (viii) intuitive graphical user interfaces to access the aforementioned functionalities and visualization of results. We have validated SPECTRUM using published datasets and benchmarked it against salient TDP tools. SPECTRUM provides significantly enhanced protein identification rates (91% to 177%) over its contemporaries. SPECTRUM has been implemented in MATLAB, and is freely available along with its source code and documentation at https://github.com/BIRL/SPECTRUM/.