Project description:Bacterial surface (S) layers are the outermost proteinaceous cell envelope structures found on members of nearly all taxonomic groups of bacteria and Archaea. They are composed of numerous identical subunits forming a symmetric, porous, lattice-like layer that completely covers the cell surface. The subunits are held together and attached to cell wall carbohydrates by non-covalent interactions, and they spontaneously reassemble in vitro by an entropy-driven process. Due to the low amino acid sequence similarity among S-layer proteins in general, verification of the presence of an S-layer on the bacterial cell surface usually requires electron microscopy. In lactobacilli, S-layer proteins have been detected on many but not all species. Lactobacillus S-layer proteins differ from those of other bacteria in their smaller size and high predicted pI. The positive charge in Lactobacillus S-layer proteins is concentrated in the more conserved cell wall binding domain, which can be either N- or C-terminal depending on the species. The more variable domain is responsible for the self-assembly of the monomers to a periodic structure. The biological functions of Lactobacillus S-layer proteins are poorly understood, but in some species S-layer proteins mediate bacterial adherence to host cells or extracellular matrix proteins or have protective or enzymatic functions. Lactobacillus S-layer proteins show potential for use as antigen carriers in live oral vaccine design because of their adhesive and immunomodulatory properties and the general non-pathogenicity of the species.
Project description:Diverse optogenetic tools have allowed versatile control over neural activity. Many depolarizing and hyperpolarizing tools have now been developed in multiple laboratories and tested across different preparations, presenting opportunities but also making it difficult to draw direct comparisons. This challenge has been compounded by the dependence of performance on parameters such as vector, promoter, expression time, illumination, cell type and many other variables. As a result, it has become increasingly complicated for end users to select the optimal reagents for their experimental needs. For a rapidly growing field, critical figures of merit should be formalized both to establish a framework for further development and so that end users can readily understand how these standardized parameters translate into performance. Here we systematically compared microbial opsins under matched experimental conditions to extract essential principles and identify key parameters for the conduct, design and interpretation of experiments involving optogenetic techniques.
Project description:Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications.
Project description:Computational methods for predicting protein function are of great significance in understanding biological mechanisms and treating complex diseases. However, existing computational approaches of protein function prediction lack interpretability, making it difficult to understand the relations between protein structures and functions. In this study, we propose a deep learning-based solution, named DPFunc, for accurate protein function prediction with domain-guided structure information. DPFunc can detect significant regions in protein structures and accurately predict corresponding functions under the guidance of domain information. It outperforms current state-of-the-art methods and achieves a significant improvement over existing structure-based methods. Detailed analyses demonstrate that the guidance of domain information contributes to DPFunc for protein function prediction, enabling our method to detect key residues or regions in protein structures, which are closely related to their functions. In summary, DPFunc serves as an effective tool for large-scale protein function prediction, which pushes the border of protein understanding in biological systems.
Project description:The widely expressed bromodomain and extraterminal motif (BET) proteins bromodomain-containing protein 2 (BRD2), BRD3, and BRD4 are multifunctional transcriptional regulators that bind acetylated chromatin via their conserved tandem bromodomains. Small molecules that target BET bromodomains are being tested for various diseases but typically do not discern between BET family members. Genomic distributions and protein partners of BET proteins have been described, but the basis for differences in BET protein function within a given lineage remains unclear. By establishing a gene knockout-rescue system in a Brd2-null erythroblast cell line, here we compared a series of mutant and chimeric BET proteins for their ability to modulate cell growth, differentiation, and gene expression. We found that the BET N-terminal halves bearing the bromodomains convey marked differences in protein stability but do not account for specificity in BET protein function. Instead, when BET proteins were expressed at comparable levels, their specificity was largely determined by the C-terminal half. Remarkably, a chimeric BET protein comprising the N-terminal half of the structurally similar short BRD4 isoform (BRD4S) and the C-terminal half of BRD2 functioned similarly to intact BRD2. We traced part of the BRD2-specific activity to a previously uncharacterized short segment predicted to harbor a coiled-coil (CC) domain. Deleting the CC segment impaired BRD2's ability to restore growth and differentiation, and the CC region functioned in conjunction with the adjacent ET domain to impart BRD2-like activity onto BRD4S. In summary, our results identify distinct BET protein domains that regulate protein turnover and biological activities.
Project description:Endosperm transfer cells (ETC) are one of four main types of cells in endosperm. A characteristic feature of ETC is the presence of cell wall in-growths that create an enlarged plasma membrane surface area. This specialized cell structure is important for the specific function of ETC, which is to transfer nutrients from maternal vascular tissue to endosperm. ETC-specific genes are of particular interest to plant biotechnologists, who use genetic engineering to improve grain quality and yield characteristics of important field crops. The success of molecular biology-based approaches to manipulating ETC function is dependent on a thorough understanding of the functions of ETC-specific genes and ETC-specific promoters. The aim of this review is to summarize the existing data on structure and function of ETC-specific genes and their products. Potential applications of ETC-specific genes, and in particular their promoters for biotechnology will be discussed.
Project description:One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.
Project description:Coronaviruses are the paradigm of emerging 21st century zoonotic viruses, triggering numerous outbreaks and a severe global health crisis. The current COVID-19 pandemic caused by SARS-CoV-2 has affected more than 51 million people across the globe as of 12 November 2020. The crown-like spikes on the surface of the virion are the unique structural feature of viruses in the family Coronaviridae. The spike (S) protein adopts distinct conformations while mediating entry of the virus into the host. This multifunctional protein mediates the entry process by recognizing its receptor on the host cell, followed by the fusion of the viral membrane with the host cell membrane. This review article focuses on the structural and functional comparison of S proteins of the human betacoronaviruses, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we review the current state of knowledge about receptor recognition, the membrane fusion mechanism, structural epitopes, and glycosylation sites of the S proteins of these viruses. We further discuss various vaccines and other therapeutics such as monoclonal antibodies, peptides, and small molecules based on the S protein of these three viruses.
Project description:Therapeutic proteins continue to yield revolutionary new treatments for a growing spectrum of human disease, but the development of these powerful drugs requires solving a unique set of challenges. For instance, it is increasingly apparent that mitigating potential anti-therapeutic immune responses, driven by molecular recognition of a therapeutic protein's peptide fragments, may be best accomplished early in the drug development process. One may eliminate immunogenic peptide fragments by mutating the cognate amino acid sequences, but deimmunizing mutations are constrained by the need for a folded, stable, and functional protein structure. These two concerns may be competing, as the mutations that are best at reducing immunogenicity often involve amino acids that are substantially different physicochemically. We develop a novel approach, called EpiSweep, that simultaneously optimizes both concerns. Our algorithm identifies sets of mutations making such Pareto optimal trade-offs between structure and immunogenicity, embodied by a molecular mechanics energy function and a T-cell epitope predictor, respectively. EpiSweep integrates structure-based protein design, sequence-based protein deimmunization, and algorithms for finding the Pareto frontier of a design space. While structure-based protein design is NP-hard, we employ integer programming techniques that are efficient in practice. Furthermore, EpiSweep only invokes the optimizer once per identified Pareto optimal design. We show that EpiSweep designs of regions of the therapeutics erythropoietin and staphylokinase are predicted to outperform previous experimental efforts. We also demonstrate EpiSweep's capacity for deimmunization of the entire proteins, case analyses involving dozens of predicted epitopes, and tens of thousands of unique side-chain interactions. Ultimately, Epi-Sweep is a powerful protein design tool that guides the protein engineer toward the most promising immunotolerant biotherapeutic candidates.
Project description:Notophthalmus viridescens (Red-spotted Newt) possess amazing capabilities to regenerate their organs and other tissues. Previously, using a de novo assembly of the newt transcriptome combined with proteomic validation, our group identified a novel family of five protein members expressed in adult tissues during regeneration in Notophthalmus viridescens. The presence of a putative signal peptide suggests that all these proteins are secretory in nature. Here we employed iterative threading assembly refinement (I-TASSER) server to generate three-dimensional structure of these novel Newt proteins and predicted their function. Our data suggests that these proteins could act as ion transporters, and be involved in redox reaction(s). Due to absence of transgenic approaches in N. viridescens, and conservation of genetic machinery across species, we generated transgenic Drosophila melanogaster to misexpress these genes. Expression of 2775 transcripts were compared between these five newly identified Newt genes. We found that genes involved in the developmental process, cell cycle, apoptosis, and immune response are among those that are highly enriched. To validate the RNA Seq. data, expression of six highly regulated genes were verified using real time Quantitative Polymerase Chain Reaction (RT-qPCR). These graded gene expression patterns provide insight into the function of novel protein family identified in Newt, and layout a map for future studies in the field.