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The expanding number of members in the various human heat shock protein (HSP) families and the inconsistencies in their nomenclature have often led to confusion. Here, we propose new guidelines for the nomenclature of the human HSP families, HSPH (HSP110), HSPC (HSP90), HSPA (HSP70), DNAJ (HSP40), and HSPB (small HSP) as well as for the human chaperonin families HSPD/E (HSP60/HSP10) and CCT (TRiC). The nomenclature is based largely on the more consistent nomenclature assigned by the HUGO Gene Nomenclature Committee and used in the National Center of Biotechnology Information Entrez Gene database for the heat shock genes. In addition to this nomenclature, we provide a list of the human Entrez Gene IDs and the corresponding Entrez Gene IDs for the mouse orthologs.

Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.SignalP 5.0 improves proteome-wide detection of signal peptides across all organisms and can distinguish between different types of signal peptides in prokaryotes.

Recent proteome-wide screening approaches have provided a wealth of information about interacting proteins in various organisms. To test for a potential association between protein connectivity and the amount of predicted structural disorder, the disorder propensities of proteins with various numbers of interacting partners from four eukaryotic organisms (Caenorhabditis elegans, Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens) were investigated. The results of PONDR VL-XT disorder analysis show that for all four studied organisms, hub proteins, defined here as those that interact with > or = 10 partners, are significantly more disordered than end proteins, defined here as those that interact with just one partner. The proportion of predicted disordered residues, the average disorder score, and the number of predicted disordered regions of various lengths were higher overall in hubs than in ends. A binary classification of hubs and ends into ordered and disordered subclasses using the consensus prediction method showed a significant enrichment of wholly disordered proteins and a significant depletion of wholly ordered proteins in hubs relative to ends in worm, fly, and human. The functional annotation of yeast hubs and ends using GO categories and the correlation of these annotations with disorder predictions demonstrate that proteins with regulation, transcription, and development annotations are enriched in disorder, whereas proteins with catalytic activity, transport, and membrane localization annotations are depleted in disorder. The results of this study demonstrate that intrinsic structural disorder is a distinctive and common characteristic of eukaryotic hub proteins, and that disorder may serve as a determinant of protein interactivity.

The CRISPR (clustered regularly interspaced short palindromic repeat) system provides bacteria with an adaptive immune response. DNA captured from viruses and plasmids by CRISPR-associated protein 1 (Cas1) is used by bacteria to target the invaders' for destruction. Silas et al. discover that certain classes of the Cas1 gene are fused to a reverse transcriptase gene ( RT-Cas1 ) (see the Perspective by Sontheimer and Marraffini). These RT-Cas1 proteins are able to capture and directly incorporate both DNA and RNA into CRISPR loci. RT-Cas1 systems could be effective against parasitic RNA species, or even to modulate bacterial gene expression. Science , this issue p. 10.1126/science.aad4234 ; see also p. 920 A reverse transcriptase activity captures and introduces RNA directly into CRISPR loci. CRISPR systems mediate adaptive immunity in diverse prokaryotes. CRISPR-associated Cas1 and Cas2 proteins have been shown to enable adaptation to new threats in type I and II CRISPR systems by the acquisition of short segments of DNA (spacers) from invasive elements. In several type III CRISPR systems, Cas1 is naturally fused to a reverse transcriptase (RT). In the marine bacterium Marinomonas mediterranea (MMB-1), we showed that a RT-Cas1 fusion protein enables the acquisition of RNA spacers in vivo in a RT-dependent manner. In vitro, the MMB-1 RT-Cas1 and Cas2 proteins catalyze the ligation of RNA segments into the CRISPR array, which is followed by reverse transcription. These observations outline a host-mediated mechanism for reverse information flow from RNA to DNA.

CRISPR-Cas9 systems have been causing a revolution in biology. Harrington et al. describe the discovery and technological implementation of an additional type of CRISPR system based on an extracompact effector protein, Cas14. Metagenomics data, particularly from uncultivated samples, uncovered the CRISPR-Cas14 systems containing all the components necessary for adaptive immunity in prokaryotes. At half the size of class 2 CRISPR effectors, Cas14 appears to target single-stranded DNA without class 2 sequence restrictions. By leveraging this activity, a fast and high-fidelity nucleic acid detection system enabled detection of single-nucleotide polymorphisms. Science , this issue p. 839 Identification, characterization, and technological implementation of additional archaea-derived CRISPR-Cas14 systems are described. CRISPR-Cas systems provide microbes with adaptive immunity to infectious nucleic acids and are widely employed as genome editing tools. These tools use RNA-guided Cas proteins whose large size (950 to 1400 amino acids) has been considered essential to their specific DNA- or RNA-targeting activities. Here we present a set of CRISPR-Cas systems from uncultivated archaea that contain Cas14, a family of exceptionally compact RNA-guided nucleases (400 to 700 amino acids). Despite their small size, Cas14 proteins are capable of targeted single-stranded DNA (ssDNA) cleavage without restrictive sequence requirements. Moreover, target recognition by Cas14 triggers nonspecific cutting of ssDNA molecules, an activity that enables high-fidelity single-nucleotide polymorphism genotyping (Cas14-DETECTR). Metagenomic data show that multiple CRISPR-Cas14 systems evolved independently and suggest a potential evolutionary origin of single-effector CRISPR-based adaptive immunity.

We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB) with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be considered as pre-training for various applications of deep learning in bioinformatics. The related data is available at Life Language Processing Website: http://llp.berkeley.edu and Harvard Dataverse: http://dx.doi.org/10.7910/DVN/JMFHTN.

Metacaspases are cysteine-dependent proteases found in protozoa, fungi and plants and are distantly related to metazoan caspases. Although metacaspases share structural properties with those of caspases, they lack Asp specificity and cleave their targets after Arg or Lys residues. Studies performed over the past 10 years have demonstrated that metacaspases are multifunctional proteases essential for normal physiology of non-metazoan organisms. This article provides a comprehensive overview of the metacaspase function and molecular regulation during programmed cell death, stress and cell proliferation, as well as an analysis of the first metacaspase-mediated proteolytic pathway. To prevent further misapplication of caspase-specific molecular probes for measuring and inhibiting metacaspase activity, we provide a list of probes suitable for metacaspases.

Background Nitrogen uptake, reallocation within the plant, and between subcellular compartments involves ammonium, nitrate and peptide transporters. Ammonium transporters are separated into two distinct families (AMT1 and AMT2), each comprised of five members on average in angiosperms. Nitrate transporters also form two discrete families (NRT1 and NRT2), with angiosperms having four NRT2s, on average. NRT1s share an evolutionary history with peptide transporters (PTRs). The NRT1/PTR family in land plants usually has more than 50 members and contains also members with distinct activities, such as glucosinolate and abscisic acid transport. Results Phylogenetic reconstructions of each family across 20 land plant species with available genome sequences were supplemented with subcellular localization and transmembrane topology predictions. This revealed that both AMT families diverged prior to the separation of bryophytes and vascular plants forming two distinct clans, designated as supergroups, each. Ten supergroups were identified for the NRT1/PTR family. It is apparent that nitrate and peptide transport within the NRT1/PTR family is polyphyletic, that is, nitrate and/or peptide transport likely evolved multiple times within land plants. The NRT2 family separated into two distinct clans early in vascular plant evolution. Subsequent duplications occurring prior to the eudicot/monocot separation led to the existence of two AMT1, six AMT2, 31 NRT1/PTR, and two NRT2 clans, designated as groups. Conclusion Phylogenetic separation of groups suggests functional divergence within the angiosperms for each family. Distinct groups within the NRT1/PTR family appear to separate peptide and nitrate transport activities as well as other activities contained within the family, for example nitrite transport. Conversely, distinct activities, such as abscisic acid and glucosinolate transport, appear to have recently evolved from nitrate transporters.

Members of the Oxa1 superfamily perform membrane protein insertion in bacteria, the eukaryotic endoplasmic reticulum (ER), and endosymbiotic organelles. Here, we review recent structures of the three ER-resident insertases and discuss the extent to which structure and function are conserved with their bacterial counterpart YidC. Recent structures of eukaryotic membrane protein insertases of the Oxa1 superfamily reveal a conserved protein module and common mechanistic principles that enable membrane insertion of a diverse set of substrates.

Activation of innate immunity by membrane-localized receptors is conserved across eukaryotes. Plant genomes contain hundreds of such receptor-like genes and those encoding proteins with an extracellular leucine-rich repeat (LRR) domain represent the largest family. Here, we develop a high-throughput approach to study LRR receptor-like genes on a genome-wide scale. In total, 257 tobacco rattle virus-based constructs are generated to target 386 of the 403 identified LRR receptor-like genes in Nicotiana benthamiana for silencing. Using this toolkit, we identify the LRR receptor-like protein Response to XEG1 (RXEG1) that specifically recognizes the glycoside hydrolase 12 protein XEG1. RXEG1 associates with XEG1 via the LRR domain in the apoplast and forms a complex with the LRR receptor-like kinases BAK1 and SOBIR1 to transduce the XEG1-induced defense signal. Thus, this genome-wide silencing assay is demonstrated to be an efficient toolkit to pinpoint new immune receptors, which will contribute to developing durable disease resistance. The role of most plant leucine-rich repeat (LRR) receptors in innate immunity is unknown. Here, the authors develop virus-based constructs to silence LRR receptor-like genes in the Nicotiana benthamiana genome and identify Response to XEG1 that specifically recognizes the glycoside hydrolase 12 protein XEG1.