Loss of C2orf69 defines a fatal autoinflammatory syndrome in humans and zebrafish that evokes a glycogen-storage-associated mitochondriopathy.

Human C2orf69 is an evolutionarily conserved gene whose function is unknown. Here, we report eight unrelated families from which 20 children presented with a fatal syndrome consisting of severe autoinflammation and progredient leukoencephalopathy with recurrent seizures; 12 of these subjects, whose DNA was available, segregated homozygous loss-of-function C2orf69 variants. C2ORF69 bears homology to esterase enzymes, and orthologs can be found in most eukaryotic genomes, including that of unicellular phytoplankton. We found that endogenous C2ORF69 (1) is loosely bound to mitochondria, (2) affects mitochondrial membrane potential and oxidative respiration in cultured neurons, and (3) controls the levels of the glycogen branching enzyme 1 (GBE1) consistent with a glycogen-storage-associated mitochondriopathy. We show that CRISPR-Cas9-mediated inactivation of zebrafish C2orf69 results in lethality by 8 months of age due to spontaneous epileptic seizures, which is preceded by persistent brain inflammation. Collectively, our results delineate an autoinflammatory Mendelian disorder of C2orf69 deficiency that disrupts the development/homeostasis of the immune and central nervous systems.

Identification and engineering of 32 membered antifungal macrolactone notonesomycins.

Notonesomycin A is a 32-membered bioactive glycosylated macrolactone known to be produced by Streptomyces aminophilus subsp. notonesogenes 647-AV1 and S. aminophilus DSM 40186. In a high throughput antifungal screening campaign, we identified an alternative notonesomycin A producing strain, Streptomyces sp. A793, and its biosynthetic gene cluster. From this strain, we further characterized a new more potent antifungal non-sulfated analogue, named notonesomycin B. Through CRISPR-Cas9 engineering of the biosynthetic gene cluster, we were able to increase the production yield of notonesomycin B by up to 18-fold as well as generate a strain that exclusively produces this analogue.

Single-residue posttranslational modification sites at the N-terminus, C-terminus or in-between: To be or not to be exposed for enzyme access.

Many protein posttranslational modifications (PTMs) are the result of an enzymatic reaction. The modifying enzyme has to recognize the substrate protein's sequence motif containing the residue(s) to be modified; thus, the enzyme's catalytic cleft engulfs these residue(s) and the respective sequence environment. This residue accessibility condition principally limits the range where enzymatic PTMs can occur in the protein sequence. Non-globular, flexible, intrinsically disordered segments or large loops/accessible long side chains should be preferred whereas residues buried in the core of structures should be void of what we call canonical, enzyme-generated PTMs. We investigate whether PTM sites annotated in UniProtKB (with MOD_RES/LIPID keys) are situated within sequence ranges that can be mapped to known 3D structures. We find that N- or C-termini harbor essentially exclusively canonical PTMs. We also find that the overwhelming majority of all other PTMs are also canonical though, later in the protein's life cycle, the PTM sites can become buried due to complex formation. Among the remaining cases, some can be explained (i) with autocatalysis, (ii) with modification before folding or after temporary unfolding, or (iii) as products of interaction with small, diffusible reactants. Others require further research how these PTMs are mechanistically generated in vivo.

Conservation of the extended substrate specificity profiles among homologous granzymes across species.

Granzymes are structurally related serine proteases involved in cell death and immunity. To date four out of five human granzymes have assigned orthologs in mice; however for granzyme H, no murine ortholog has been suggested and its role in cytotoxicity remains controversial. Here, we demonstrate that, as is the case for granzyme C, human granzyme H is an inefficient cytotoxin that together with their similar pattern of GrB divergence and functional similarity strongly hint to their orthologous relationship. Besides analyzing the substrate specificity profile of granzyme H by substrate phage display, substrate cleavage susceptibility of human granzyme H and mouse granzyme C was assessed on a proteome-wide level. The extended specificity profiles of granzymes C and H (i.e. beyond cleavage positions P4-P4') match those previously observed for granzyme B. We demonstrate conservation of these extended specificity profiles among various granzymes as granzyme B cleavage susceptibility of an otherwise granzyme H/C specific cleavage site can simply be conferred by altering the P1-residue to aspartate, the preferred P1-residue of granzyme B. Our results thus indicate a conserved, but hitherto underappreciated specificity-determining role of extended protease-substrate contacts in steering cleavage susceptibility.

Tachyon search speeds up retrieval of similar sequences by several orders of magnitude.

UNLABELLED: The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic. AVAILABILITY AND IMPLEMENTATION: The tool is publicly accessible as a webserver at http://tachyon.bii.a-star.edu.sg and can also be accessed programmatically through SOAP.

ANNIE: integrated de novo protein sequence annotation.

Function prediction of proteins with computational sequence analysis requires the use of dozens of prediction tools with a bewildering range of input and output formats. Each of these tools focuses on a narrow aspect and researchers are having difficulty obtaining an integrated picture. ANNIE is the result of years of close interaction between computational biologists and computer scientists and automates an essential part of this sequence analytic process. It brings together over 20 function prediction algorithms that have proven sufficiently reliable and indispensable in daily sequence analytic work and are meant to give scientists a quick overview of possible functional assignments of sequence segments in the query proteins. The results are displayed in an integrated manner using an innovative AJAX-based sequence viewer. ANNIE is available online at: http://annie.bii.a-star.edu.sg. This website is free and open to all users and there is no login requirement.

Functional Classification of Super-Large Families of Enzymes Based on Substrate Binding Pocket Residues for Biocatalysis and Enzyme Engineering Applications.

Large enzyme families such as the groups of zinc-dependent alcohol dehydrogenases (ADHs), long chain alcohol oxidases (AOxs) or amine dehydrogenases (AmDHs) with, sometimes, more than one million sequences in the non-redundant protein database and hundreds of experimentally characterized enzymes are excellent cases for protein engineering efforts aimed at refining and modifying substrate specificity. Yet, the backside of this wealth of information is that it becomes technically difficult to rationally select optimal sequence targets as well as sequence positions for mutagenesis studies. In all three cases, we approach the problem by starting with a group of experimentally well studied family members (including those with available 3D structures) and creating a structure-guided multiple sequence alignment and a modified phylogenetic tree (aka binding site tree) based just on a selection of potential substrate binding residue positions derived from experimental information (not from the full-length sequence alignment). Hereupon, the remaining, mostly uncharacterized enzyme sequences can be mapped; as a trend, sequence grouping in the tree branches follows substrate specificity. We show that this information can be used in the target selection for protein engineering work to narrow down to single suitable sequences and just a few relevant candidate positions for directed evolution towards activity for desired organic compound substrates. We also demonstrate how to find the closest thermophile example in the dataset if the engineering is aimed at achieving most robust enzymes.

Conserved sequence motifs in human TMTC1, TMTC2, TMTC3, and TMTC4, new O-mannosyltransferases from the GT-C/PMT clan, are rationalized as ligand binding sites.

BACKGROUND: The human proteins TMTC1, TMTC2, TMTC3 and TMTC4 have been experimentally shown to be components of a new O-mannosylation pathway. Their own mannosyl-transferase activity has been suspected but their actual enzymatic potential has not been demonstrated yet. So far, sequence analysis of TMTCs has been compromised by evolutionary sequence divergence within their membrane-embedded N-terminal region, sequence inaccuracies in the protein databases and the difficulty to interpret the large functional variety of known homologous proteins (mostly sugar transferases and some with known 3D structure). RESULTS: Evolutionary conserved molecular function among TMTCs is only possible with conserved membrane topology within their membrane-embedded N-terminal regions leading to the placement of homologous long intermittent loops at the same membrane side. Using this criterion, we demonstrate that all TMTCs have 11 transmembrane regions. The sequence segment homologous to Pfam model DUF1736 is actually just a loop between TM7 and TM8 that is located in the ER lumen and that contains a small hydrophobic, but not membrane-embedded helix. Not only do the membrane-embedded N-terminal regions of TMTCs share a common fold and 3D structural similarity with subgroups of GT-C sugar transferases. The conservation of residues critical for catalysis, for binding of a divalent metal ion and of the phosphate group of a lipid-linked sugar moiety throughout enzymatically and structurally well-studied GT-Cs and sequences of TMTCs indicates that TMTCs are actually sugar-transferring enzymes. We present credible 3D structural models of all four TMTCs (derived from their closest known homologues 5ezm/5f15) and find observed conserved sequence motifs rationalized as binding sites for a metal ion and for a dolichyl-phosphate-mannose moiety. CONCLUSIONS: With the results from both careful sequence analysis and structural modelling, we can conclusively say that the TMTCs are enzymatically active sugar transferases belonging to the GT-C/PMT superfamily. The DUF1736 segment, the loop between TM7 and TM8, is critical for catalysis and lipid-linked sugar moiety binding. Together with the available indirect experimental data, we conclude that the TMTCs are not only part of an O-mannosylation pathway in the endoplasmic reticulum of upper eukaryotes but, actually, they are the sought mannosyl-transferases.

Factors influencing SARS-CoV-2 transmission and outbreak control measures in densely populated settings.

Starting with a handful of SARS-CoV-2 infections in dormitory residents in late March 2020, rapid transmission in their dense living environments ensued and by October 2020, more than 50,000 acute infections were identified across various dormitories in Singapore. The aim of the study is to identify combination of factors facilitating SARS-CoV-2 transmission and the impact of control measures in a dormitory through extensive epidemiological, serological and phylogenetic investigations, supported by simulation models. Our findings showed that asymptomatic cases and symptomatic cases who did not seek medical attention were major drivers of the outbreak. Furthermore, each resident had about 30 close contacts and each infected resident spread to 4.4 (IQR 3.5-5.3) others at the start of the outbreak. The final attack rate of the current outbreak was 76.2% (IQR 70.6-98.0%) and could be reduced by further 10% under a modified dormitory housing condition. These findings are important when designing living environments in a post COVID-19 future to reduce disease spread and facilitate rapid implementation of outbreak control measures.

Epidemiological, Clinical, and Phylogenetic Characteristics of the First SARS-CoV-2 Transmission in a Nursing Home of Singapore: A Prospective Observational Investigation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has resulted in a significant burden among nursing home facilities globally. This prospective observational cohort study aims to define the potential sources of introduction and characteristics of SARS-CoV-2 transmission of the first nursing home facility in Singapore. An epidemiological serial point-prevalence survey of SARS-CoV-2 was conducted among 108 residents and 56 healthcare staff (HCS). In the current study, 14 (13%) residents and two (3.6%) HCS were diagnosed with coronavirus disease 2019 (COVID-19), with a case fatality rate (CFR) of 28.6% (4/14) among the residents. The median age of the infected residents was 86.5 [interquartile range (IQR) 78.5-88] and 85.7% were women. Five residents were symptomatic (35.7%) and the others were asymptomatic (64.3%). A higher proportion of residents who succumbed to COVID-19 had hypertension than those who recovered. The SARS-CoV-2 whole-genome sequencing showed lineage B.6 which is rare globally but common regionally during the early phase of the pandemic. Household transmission is a potential source of introduction into the nursing home, with at least six epidemiologically linked secondary cases. Male residents were less implicated due to the staff segregation plan by block. Among residents, a higher proportion of the non-survivors were asymptomatic and had hypertension compared with survivors.

Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset.

BACKGROUND: Algorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable. RESULTS: First, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended default parameters, the programs tested are producing a wide range of predictions at different levels of specificity and sensitivity. We identify settings, in which the different predictors have the same false positive rate. We assess conditions when sets of predictors can be run together to derive consensus or complementary predictions. This is useful in the framework of proteome-wide applications where high specificity is required such as in our in-house sequence analysis pipeline and the ANNIE webserver. CONCLUSIONS: This work identifies parameter settings and thresholds for a selection of disorder predictors to produce comparable results at a desired level of specificity over a newly derived benchmark dataset that accounts equally for ordered and disordered regions of different lengths.

All that glitters is not gold--founder effects complicate associations of flu mutations to disease severity.

BACKGROUND: The recent 2009 (H1N1) influenza A pandemic saw a rapid spread of the virus to essentially all parts of the world. In the course of its evolution, the virus acquired many mutations, some of which have been investigated in the context of increased severity due to high occurrences in fatal cases. For example, statements such as: "42.9% of individuals who died from laboratory-confirmed cases of the pandemic (H1N1) were infected with the hemagglutinin (HA) Q310 H mutant virus." give the impression that HA-Q310 H would be highly dangerous or important, while careful consideration of all available data suggests that this is unlikely to be the case. RESULTS: We compare the mutations HA-Q310 H, PB2-K340N, HA-D239N and HA-D239G using whole genome phylogenetic trees, structural modeling in their 3 D context and complete epidemiological data from sequences to clinical outcomes. HA-Q310 H and PB2-K340N appear as isolated subtrees in the phylogenetic analysis pointing to founder effects which is consistent with their clustered temporal appearance as well as the lack of an immediate structural basis that could explain a change of phenotypes. Considering the prevailing viral genomic background, shared origin of samples (all from the city of Sao Paulo) and narrow temporal window (all death case samples within 1 month), it becomes clear that HA-Q310 H was actually a generally common mutation in the region at that time which could readily explain its increased occurrence among the few analyzed fatal cases without requiring necessarily an association with severity. In further support of this, we highlight 3 mild cases with the HA-Q310 H mutation. CONCLUSIONS: We argue that claims of severity of any current and future flu mutation need to be critically considered in the light of phylogenetic, structural and detailed epidemiological data to distinguish increased occurrence due to possible founder effects rather than real phenotypic changes.

Role of the amino acid sequence in domain swapping of the B1 domain of protein G.

Substitution of four amino acid residues (L5V,F30V, Y33F,A34F) in the B1 domain of the immunoglobulin G binding protein (GB1) leads to the formation of a swapped dimer, shown to be in equilibrium with a native-like monomeric state of the protein (Byeon et al., J Mol Biol 2003;333:141-152). In this study, we employ protein design calculations and molecular dynamics simulations to investigate the role of these substitutions in fostering the swapping reaction. DESIGNER, a fully automatic procedure for computing the amino acid sequences likely to stabilize a given backbone structure is used to investigate the effect of the four substitutions on the stability of the wild type native monomeric conformation. Results indicate that at least three of these substitutions (L5V,F30V, A34F) have a destabilizing effect. The L5V forms destabilizing interactions with surrounding residues, whereas F30V causes local strain due to unfavorable interactions with its own backbone. A dual role in the swapping reaction is played by A34F. It destabilizes the monomer conformation while stabilizing the swapped dimer. Our calculations find an energetically favorable conformation for the 34F side chain in the core of the monomer, but only at the expense of forcing the wild type W43 side chain into a highly strained rotamer, and forming unfavorable interactions with both W43 and V54. Although detailed calculations could not be performed on the swapped dimer, due to the lower accuracy of the model, analysis revealed that the 34F side chain from both subunits are tightly packed against each other in the dimer core, suggesting that their replacement by the smaller Ala, as in the wild type, would be highly destabilizing through the creation of a large internal cavity possibly accompanied by a substantial conformational change. Analysis of room temperature molecular dynamics (MD) simulations of the wild type and the modeled quadruple mutant structures reveals that the latter structure fluctuates more than its wild type counterpart. In addition, its C-terminal beta-hairpin, which is exchanged in the swapping reaction, undergoes a conformation change, which pushes it further away from the remainder of the protein. Simulations at higher temperature (450 K) show that the quadruple mutant unfolds earlier and more completely than the wild type following a sequence of events that is compatible with the description of the highly fluctuating monomeric state of this mutant observed by NMR. Our findings thus support the notion that domain swapping in GB1 is fostered by three main factors: a decrease in stability and increased flexibility of the monomer conformation, concomitant with stabilization of the swapped dimer conformation through new interactions that have no counterparts in the monomer.

Towards complete sets of farnesylated and geranylgeranylated proteins.

Three different prenyltransferases attach isoprenyl anchors to C-terminal motifs in substrate proteins. These lipid anchors serve for membrane attachment or protein-protein interactions in many pathways. Although well-tolerated selective prenyltransferase inhibitors are clinically available, their mode of action remains unclear since the known substrate sets of the various prenyltransferases are incomplete. The Prenylation Prediction Suite (PrePS) has been applied for large-scale predictions of prenylated proteins. To prioritize targets for experimental verification, we rank the predictions by their functional importance estimated by evolutionary conservation of the prenylation motifs within protein families. The ranked lists of predictions are accessible as PRENbase (http://mendel.imp.univie.ac.at/sat/PrePS/PRENbase) and can be queried for verification status, type of modifying enzymes (anchor type), and taxonomic distribution. Our results highlight a large group of plant metal-binding chaperones as well as several newly predicted proteins involved in ubiquitin-mediated protein degradation, enriching the known functional repertoire of prenylated proteins. Furthermore, we identify two possibly prenylated proteins in Mimivirus. The section HumanPRENbase provides complete lists of predicted prenylated human proteins-for example, the list of farnesyltransferase targets that cannot become substrates of geranylgeranyltransferase 1 and, therefore, are especially affected by farnesyltransferase inhibitors (FTIs) used in cancer and anti-parasite therapy. We report direct experimental evidence verifying the prediction of the human proteins Prickle1, Prickle2, the BRO1 domain-containing FLJ32421 (termed BROFTI), and Rab28 (short isoform) as exclusive farnesyltransferase targets. We introduce PRENbase, a database of large-scale predictions of protein prenylation substrates ranked by evolutionary conservation of the motif. Experimental evidence is presented for the selective farnesylation of targets with an evolutionary conserved modification site.

Isolation and Identification of an Anthracimycin Analogue from Nocardiopsis kunsanensis, a Halophile from a Saltern, by Genomic Mining Strategy.

Modern medicine is unthinkable without antibiotics; yet, growing issues with microbial drug resistance require intensified search for new active compounds. Natural products generated by Actinobacteria have been a rich source of candidate antibiotics, for example anthracimycin that, so far, is only known to be produced by Streptomyces species. Based on sequence similarity with the respective biosynthetic cluster, we sifted through available microbial genome data with the goal to find alternative anthracimycin-producing organisms. In this work, we report about the prediction and experimental verification of the production of anthracimycin derivatives by Nocardiopsis kunsanensis, a non-Streptomyces actinobacterial microorganism. We discovered N. kunsanensis to predominantly produce a new anthracimycin derivative with methyl group at C-8 and none at C-2, labeled anthracimycin BII-2619, besides a minor amount of anthracimycin. It displays activity against Gram-positive bacteria with similar low level of mammalian cytotoxicity as that of anthracimycin.

The Geographic Variation of Surveillance and Zoonotic Spillover Potential of Influenza Viruses in Domestic Poultry and Swine.

BACKGROUND: Avian and swine influenza viruses circulate worldwide and pose threats to both animal and human health. The design of global surveillance strategies is hindered by information gaps on the geospatial variation in virus emergence potential and existing surveillance efforts. METHODS: We developed a spatial framework to quantify the geographic variation in outbreak emergence potential based on indices of potential for animal-to-human and secondary human-to-human transmission. We then compared our resultant raster model of variation in emergence potential with the global distribution of recent surveillance efforts from 359105 reports of surveillance activities. RESULTS: Our framework identified regions of Southeast Asia, Eastern Europe, Central America, and sub-Saharan Africa with high potential for influenza virus spillover. In the last 15 years, however, we found that 78.43% and 49.01% of high-risk areas lacked evidence of influenza virus surveillance in swine and domestic poultry, respectively. CONCLUSIONS: Our work highlights priority areas where improved surveillance and outbreak mitigation could enhance pandemic preparedness strategies.

The Recipe for Protein Sequence-Based Function Prediction and Its Implementation in the ANNOTATOR Software Environment.

As biomolecular sequencing is becoming the main technique in life sciences, functional interpretation of sequences in terms of biomolecular mechanisms with in silico approaches is getting increasingly significant. Function prediction tools are most powerful for protein-coding sequences; yet, the concepts and technologies used for this purpose are not well reflected in bioinformatics textbooks. Notably, protein sequences typically consist of globular domains and non-globular segments. The two types of regions require cardinally different approaches for function prediction. Whereas the former are classic targets for homology-inspired function transfer based on remnant, yet statistically significant sequence similarity to other, characterized sequences, the latter type of regions are characterized by compositional bias or simple, repetitive patterns and require lexical analysis and/or empirical sequence pattern-function correlations. The recipe for function prediction recommends first to find all types of non-globular segments and, then, to subject the remaining query sequence to sequence similarity searches. We provide an updated description of the ANNOTATOR software environment as an advanced example of a software platform that facilitates protein sequence-based function prediction.

Beware of moving targets: reference proteome content fluctuates substantially over the years.

Reference proteomes are generated by increasingly sophisticated annotation pipelines as part of regular genome build releases; yet, the corresponding changes in reference proteomes' content are dramatic. In the history of the NCBI-curated human proteome, the total number of entries has remained roughly constant but approximately half of the proteins from the 2003 build 33 are no longer represented by entries in current releases, while about the same number of new proteins have been added (for sequence identity thresholds 50-90%). Although mostly hypothetical proteins are affected, there are also spectacular cases of entry removal/addition of well studied proteins. The changes between the 2003 and recent human proteomes are in a similar order of magnitude as the differences between recent human and chimpanzee proteome releases. As an application example, we show that the proteome fluctuations affect the interpretation (about 74% of hits) of organelle-specific mass-spectrometry data. Although proteome quality tends to improve with more recent releases as, for example, the fraction of proteins with functional annotation has increased over time, existing evidence implies that, apparently, the proteome content still remains incomplete, not just pertaining to isoforms/sequence variants but also to proteins and their families that are clearly distinct.

Integrated tools for biomolecular sequence-based function prediction as exemplified by the ANNOTATOR software environment.

Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.