Targeting the GPI transamidase subunit GPAA1 abrogates the CD24 immune checkpoint in ovarian cancer

CD24 is frequently overexpressed in ovarian cancer and promotes immune evasion by interacting with its receptor Siglec10, present on tumor-associated macrophages, providing a "don't eat me" signal that prevents targeting and phagocytosis by macrophages. Factors promoting CD24 expression could represent novel immunotherapeutic targets for ovarian cancer. Here, using a genome-wide CRISPR knockout screen, we identify GPAA1 (glycosylphosphatidylinositol anchor attachment 1), a factor that catalyzes the attachment of a glycosylphosphatidylinositol (GPI) lipid anchor to substrate proteins, as a positive regulator of CD24 cell surface expression. Genetic ablation of GPAA1 abolishes CD24 cell surface expression, enhances macrophage-mediated phagocytosis, and inhibits ovarian tumor growth in mice. GPAA1 shares structural similarities with aminopeptidases. Consequently, we show that bestatin, a clinically advanced aminopeptidase inhibitor, binds to GPAA1 and blocks GPI attachment, resulting in reduced CD24 cell surface expression, increased macrophage-mediated phagocytosis, and suppressed growth of ovarian tumors. Our study highlights the potential of targeting GPAA1 as an immunotherapeutic approach for CD24+ ovarian cancers.

Global longitudinal strain and plasma biomarkers for prognosis in heart failure complicated by diabetes: a prospective observational study

BACKGROUND

Heart failure (HF) and diabetes are associated with increased incidence and worse prognosis of each other. The prognostic value of global longitudinal strain (GLS) measured by cardiovascular magnetic resonance (CMR) has not been established in HF patients with diabetes.

METHODS

In this prospective, observational study, consecutive patients (n = 315) with HF underwent CMR at 3T, including GLS, late gadolinium enhancement (LGE), native T1, and extracellular volume fraction (ECV) mapping. Plasma biomarker concentrations were measured including: N-terminal pro B-type natriuretic peptide(NT-proBNP), high-sensitivity troponin T(hs-TnT), growth differentiation factor 15(GDF-15), soluble ST2(sST2), and galectin 3(Gal-3). The primary outcome was a composite of all-cause mortality or HF hospitalisation.

RESULTS

Compared to those without diabetes (n = 156), the diabetes group (n = 159) had a higher LGE prevalence (76 vs. 60%, p < 0.05), higher T1 (1285±42 vs. 1269±42ms, p < 0.001), and higher ECV (30.5±3.5 vs. 28.8±4.1%, p < 0.001). The diabetes group had higher NT-pro-BNP, hs-TnT, GDF-15, sST2, and Gal-3. Diabetes conferred worse prognosis (hazard ratio (HR) 2.33 [95% confidence interval (CI) 1.43-3.79], p < 0.001). In multivariable Cox regression analysis including clinical markers and plasma biomarkers, sST2 alone remained independently associated with the primary outcome (HR per 1 ng/mL 1.04 [95% CI 1.02-1.07], p = 0.001). In multivariable Cox regression models in the diabetes group, both GLS and sST2 remained prognostic (GLS: HR 1.12 [95% CI 1.03-1.21], p = 0.01; sST2: HR per 1 ng/mL 1.03 [95% CI 1.00-1.06], p = 0.02).

CONCLUSIONS

Compared to HF patients without diabetes, those with diabetes have worse plasma and CMR markers of fibrosis and a more adverse prognosis. GLS by CMR is a powerful and independent prognostic marker in HF patients with diabetes.

PICLS with human cells is the first high throughput screening method for identifying novel compounds that extend lifespan

Gerontology research on anti-aging interventions with drugs could be an answer to age-related diseases, aiming at closing the gap between lifespan and healthspan. Here, we present two methods for assaying chronological lifespan in human cells: (1) a version of the classical outgrowth assay with quantitative assessment of surviving cells and (2) a version of the PICLS method (propidium iodide fluorescent-based measurement of cell death). Both methods are fast, simple to conduct, cost-effective, produce quantitative data for further analysis and can be used with diverse human cell lines. Whereas the first method is ideal for validation and testing the post-intervention reproductive potential of surviving cells, the second method has true high-throughput screening potential. The new technologies were validated with known anti-aging compounds (2,5-anhydro-D-mannitol and rapamycin). Using the high-throughput screening method, we screened a library of 162 chemical entities and identified three compounds that extend the longevity of human cells.

Generalized metabolic flux analysis framework provides mechanism-based predictions of ophthalmic complications in type 2 diabetes patients

Chronic metabolic diseases arise from changes in metabolic fluxes through biomolecular pathways and gene networks accumulated over the lifetime of an individual. While clinical and biochemical profiles present just real-time snapshots of the patients' health, efficient computation models of the pathological disturbance of biomolecular processes are required to achieve individualized mechanistic insights into disease progression. Here, we describe the Generalized metabolic flux analysis (GMFA) for addressing this gap. Suitably grouping individual metabolites/fluxes into pools simplifies the analysis of the resulting more coarse-grain network. We also map non-metabolic clinical modalities onto the network with additional edges. Instead of using the time coordinate, the system status (metabolite concentrations and fluxes) is quantified as function of a generalized extent variable (a coordinate in the space of generalized metabolites) that represents the system's coordinate along its evolution path and evaluates the degree of change between any two states on that path. We applied GMFA to analyze Type 2 Diabetes Mellitus (T2DM) patients from two cohorts: EVAS (289 patients from Singapore) and NHANES (517) from the USA. Personalized systems biology models (digital twins) were constructed. We deduced disease dynamics from the individually parameterized metabolic network and predicted the evolution path of the metabolic health state. For each patient, we obtained an individual description of disease dynamics and predict an evolution path of the metabolic health state. Our predictive models achieve an ROC-AUC in the range 0.79-0.95 (sensitivity 80-92%, specificity 62-94%) in identifying phenotypes at the baseline and predicting future development of diabetic retinopathy and cataract progression among T2DM patients within 3 years from the baseline. The GMFA method is a step towards realizing the ultimate goal to develop practical predictive computational models for diagnostics based on systems biology. This tool has potential use in chronic disease management in medical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-023-00218-x.

The First Quarter Century of the Dense Alignment Surface Transmembrane Prediction Method

The dense alignment surface (DAS) transmembrane (TM) prediction method was first published more than 25 years ago. DAS was the one of the earliest tools to discriminate TM proteins from globular ones and to predict the sequence positions of TM helices in proteins with high accuracy from their amino acid sequence alone. The algorithmic improvements that followed in 2002 (DAS-TMfilter) made it one of the best performing tools among those relying on local sequence information for TM prediction. Since then, many more experimental data about membrane proteins (including thousands of 3D structures of membrane proteins) have accumulated but there has been no significant improvement concerning performance in the area of TM helix prediction tools. Here, we report a new implementation of the DAS-TMfilter prediction web server. We reevaluated the performance of the method using a five-times-larger, updated test dataset. We found that the method performs at essentially the same accuracy as the original even without any change to the parametrization of the program despite the much larger dataset. Thus, the approach captures the physico-chemistry of TM helices well, essentially solving this scientific problem.

Did the early full genome sequencing of yeast boost gene function discovery?

BACKGROUND

Although the genome of Saccharomyces cerevisiae (S. cerevisiae) was the first one of a eukaryote organism that was fully sequenced (in 1996), a complete understanding of the potential of encoded biomolecular mechanisms has not yet been achieved. Here, we wish to quantify how far the goal of a full list of S. cerevisiae gene functions still is.

RESULTS

The scientific literature about S. cerevisiae protein-coding genes has been mapped onto the yeast genome via the mentioning of names for genomic regions in scientific publications. The match was quantified with the ratio of a given gene name's occurrences to those of any gene names in the article. We find that ~ 230 elite genes with ≥ 75 full publication equivalents (FPEs, FPE = 1 is an idealized publication referring to just a single gene) command ~ 45% of all literature. At the same time, about two thirds of the genes (each with less than 10 FPEs) are described in just 12% of the literature (in average each such gene has just ~ 1.5% of the literature of an elite gene). About 600 genes have not been mentioned in any dedicated article. Compared with other groups of genes, the literature growth rates were highest for uncharacterized or understudied genes until late nineties of the twentieth century. Yet, these growth rates deteriorated and became negative thereafter. Thus, yeast function discovery for previously uncharacterized genes has returned to the level of ~ 1980. At the same time, literature for anyhow well-studied genes (with a threshold T10 (≥ 10 FPEs) and higher) remains steadily growing.

CONCLUSIONS

Did the early full genome sequencing of yeast boost gene function discovery? The data proves that the moment of publishing the full genome in reality coincides with the onset of decline of gene function discovery for previously uncharacterized genes. If the current status of literature about yeast molecular mechanisms can be extrapolated into the future, it will take about another ~ 50 years to complete the yeast gene function list. We found that a small group of scientific journals contributed extraordinarily to publishing early reports relevant to yeast gene function discoveries.

About the dark corners in the gene function space of Escherichia coli remaining without illumination by scientific literature

BACKGROUND

Although Escherichia coli (E. coli) is the most studied prokaryote organism in the history of life sciences, many molecular mechanisms and gene functions encoded in its genome remain to be discovered. This work aims at quantifying the illumination of the E. coli gene function space by the scientific literature and how close we are towards the goal of a complete list of E. coli gene functions.

RESULTS

The scientific literature about E. coli protein-coding genes has been mapped onto the genome via the mentioning of names for genomic regions in scientific articles both for the case of the strain K-12 MG1655 as well as for the 95%-threshold softcore genome of 1324 E. coli strains with known complete genome. The article match was quantified with the ratio of a given gene name's occurrence to the mentioning of any gene names in the paper. The various genome regions have an extremely uneven literature coverage. A group of elite genes with ≥ 100 full publication equivalents (FPEs, FPE = 1 is an idealized publication devoted to just a single gene) attracts the lion share of the papers. For K-12, ~ 65% of the literature covers just 342 elite genes; for the softcore genome, ~ 68% of the FPEs is about only 342 elite gene families (GFs). We also find that most genes/GFs have at least one mentioning in a dedicated scientific article (with the exception of at least 137 protein-coding transcripts for K-12 and 26 GFs from the softcore genome). Whereas the literature growth rates were highest for uncharacterized or understudied genes until 2005-2010 compared with other groups of genes, they became negative thereafter. At the same time, literature for anyhow well-studied genes started to grow explosively with threshold T10 (≥ 10 FPEs). Typically, a body of ~ 20 actual articles generated over ~ 15 years of research effort was necessary to reach T10. Lineage-specific co-occurrence analysis of genes belonging to the accessory genome of E. coli together with genomic co-localization and sequence-analytic exploration hints previously completely uncharacterized genes yahV and yddL being associated with osmotic stress response/motility mechanisms.

CONCLUSION

If the numbers of scientific articles about uncharacterized and understudied genes remain at least at present levels, full gene function lists for the strain K-12 MG1655 and the E. coli softcore genome are in reach within the next 25-30 years. Once the literature body for a gene crosses 10 FPEs, most of the critical fundamental research risk appears overcome and steady incremental research becomes possible.

To kill or to be killed: pangenome analysis of Escherichia coli strains reveals a tailocin specific for pandemic ST131

BACKGROUND

Escherichia coli (E. coli) has been one of the most studied model organisms in the history of life sciences. Initially thought just to be commensal bacteria, E. coli has shown wide phenotypic diversity including pathogenic isolates with great relevance to public health. Though pangenome analysis has been attempted several times, there is no systematic functional characterization of the E. coli subgroups according to the gene profile.

RESULTS

Systematically scanning for optimal parametrization, we have built the E. coli pangenome from 1324 complete genomes. The pangenome size is estimated to be ~25,000 gene families (GFs). Whereas the core genome diminishes as more genomes are added, the softcore genome (≥95% of strains) is stable with ~3000 GFs regardless of the total number of genomes. Apparently, the softcore genome (with a 92% or 95% generation threshold) can define the genome of a bacterial species listing the critically relevant, evolutionarily most conserved or important classes of GFs. Unsupervised clustering of common E. coli sequence types using the presence/absence GF matrix reveals distinct characteristics of E. coli phylogroups B1, B2, and E. We highlight the bi-lineage nature of B1, the variation of the secretion and of the iron acquisition systems in ST11 (E), and the incorporation of a highly conserved prophage into the genome of ST131 (B2). The tail structure of the prophage is evolutionarily related to R2-pyocin (a tailocin) from Pseudomonas aeruginosa PAO1. We hypothesize that this molecular machinery is highly likely to play an important role in protecting its own colonies; thus, contributing towards the rapid rise of pandemic E. coli ST131.

CONCLUSIONS

This study has explored the optimized pangenome development in E. coli. We provide complete GF lists and the pangenome matrix as supplementary data for further studies. We identified biological characteristics of different E. coli subtypes, specifically for phylogroups B1, B2, and E. We found an operon-like genome region coding for a tailocin specific for ST131 strains. The latter is a potential killer weapon providing pandemic E. coli ST131 with an advantage in inter-bacterial competition and, suggestively, explains their dominance as human pathogen among E. coli strains.

The PICLS high-throughput screening method for agents extending cellular longevity identifies 2,5-anhydro-D-mannitol as novel anti-aging compound

Although aging is the biggest risk factor for human chronic (cancer, diabetic, cardiovascular, and neurodegenerative) diseases, few interventions are known besides caloric restriction and a small number of drugs (with substantial side effects) that directly address aging. Thus, there is an urgent need for new options that can generally delay aging processes and prevent age-related diseases. Cellular aging is at the basis of aging processes. Chronological lifespan (CLS) of yeast Saccharomyces cerevisiae is the well-established model system for investigating the interventions of human post-mitotic cellular aging. CLS is defined as the number of days cells remain viable in a stationary phase. We developed a new, cheap, and fast quantitative method for measuring CLS in cell cultures incubated together with various chemical agents and controls on 96-well plates. Our PICLS protocol with (1) the use of propidium iodide for fluorescent-based cell survival reading in a microplate reader and (2) total cell count measurement via OD600nm absorption from the same plate provides real high-throughput capacity. Depending on logistics, large numbers of plates can be processed in parallel so that the screening of thousands of compounds becomes feasible in a short time. The method was validated by measuring the effect of rapamycin and calorie restriction on yeast CLS. We utilized this approach for chemical agent screening. We discovered the anti-aging/geroprotective potential of 2,5-anhydro-D-mannitol (2,5-AM) and suggest its usage individually or in combination with other anti-aging interventions.

Iron Supplementation Delays Aging and Extends Cellular Lifespan through Potentiation of Mitochondrial Function

Aging is the greatest challenge to humankind worldwide. Aging is associated with a progressive loss of physiological integrity due to a decline in cellular metabolism and functions. Such metabolic changes lead to age-related diseases, thereby compromising human health for the remaining life. Thus, there is an urgent need to identify geroprotectors that regulate metabolic functions to target the aging biological processes. Nutrients are the major regulator of metabolic activities to coordinate cell growth and development. Iron is an important nutrient involved in several biological functions, including metabolism. In this study using yeast as an aging model organism, we show that iron supplementation delays aging and increases the cellular lifespan. To determine how iron supplementation increases lifespan, we performed a gene expression analysis of mitochondria, the main cellular hub of iron utilization. Quantitative analysis of gene expression data reveals that iron supplementation upregulates the expression of the mitochondrial tricarboxylic acid (TCA) cycle and electron transport chain (ETC) genes. Furthermore, in agreement with the expression profiles of mitochondrial genes, ATP level is elevated by iron supplementation, which is required for increasing the cellular lifespan. To confirm, we tested the role of iron supplementation in the AMPK knockout mutant. AMPK is a highly conserved controller of mitochondrial metabolism and energy homeostasis. Remarkably, iron supplementation rescued the short lifespan of the AMPK knockout mutant and confirmed its anti-aging role through the enhancement of mitochondrial functions. Thus, our results suggest a potential therapeutic use of iron supplementation to delay aging and prolong healthspan.

Optimizing the Parametrization of Homologue Classification in the Pan-Genome Computation for a Bacterial Species: Case Study Streptococcus pyogenes

The paradigm shift associated with the introduction of the pan-genome concept has drawn the attention from singular reference genomes toward the actual sequence diversity within organism populations, strain collections, clades, etc. A single genome is no longer sufficient to describe bacteria of interest, but instead, the genomic repertoire of all existing strains is the key to the metabolic, evolutionary, or pathogenic potential of a species. The classification of orthologous genes derived from a collection of taxonomically related genome sequences is central to bacterial pan-genome computational analysis. In this work, we present a review of methods for computing pan-genome gene clusters including their comparative analysis for the case of Streptococcus pyogenes strain genomes. We exhaustively scanned the parametrization space of the homologue searching procedures and find optimal parameters (sequence identity (60%) and coverage (50-60%) in the pairwise alignment) for the orthologous clustering of gene sequences. We find that the sequence identity threshold influences the number of gene families ~3 times stronger than the sequence coverage threshold.

Discovery of a genetic module essential for assigning left-right asymmetry in humans and ancestral vertebrates

The vertebrate left-right axis is specified during embryogenesis by a transient organ: the left-right organizer (LRO). Species including fish, amphibians, rodents and humans deploy motile cilia in the LRO to break bilateral symmetry, while reptiles, birds, even-toed mammals and cetaceans are believed to have LROs without motile cilia. We searched for genes whose loss during vertebrate evolution follows this pattern and identified five genes encoding extracellular proteins, including a putative protease with hitherto unknown functions that we named ciliated left-right organizer metallopeptide (CIROP). Here, we show that CIROP is specifically expressed in ciliated LROs. In zebrafish and Xenopus, CIROP is required solely on the left side, downstream of the leftward flow, but upstream of DAND5, the first asymmetrically expressed gene. We further ascertained 21 human patients with loss-of-function CIROP mutations presenting with recessive situs anomalies. Our findings posit the existence of an ancestral genetic module that has twice disappeared during vertebrate evolution but remains essential for distinguishing left from right in humans.

Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study

BACKGROUND

Echocardiography is the diagnostic modality for assessing cardiac systolic and diastolic function to diagnose and manage heart failure. However, manual interpretation of echocardiograms can be time consuming and subject to human error. Therefore, we developed a fully automated deep learning workflow to classify, segment, and annotate two-dimensional (2D) videos and Doppler modalities in echocardiograms.

METHODS

We developed the workflow using a training dataset of 1145 echocardiograms and an internal test set of 406 echocardiograms from the prospective heart failure research platform (Asian Network for Translational Research and Cardiovascular Trials; ATTRaCT) in Asia, with previous manual tracings by expert sonographers. We validated the workflow against manual measurements in a curated dataset from Canada (Alberta Heart Failure Etiology and Analysis Research Team; HEART; n=1029 echocardiograms), a real-world dataset from Taiwan (n=31 241), the US-based EchoNet-Dynamic dataset (n=10 030), and in an independent prospective assessment of the Asian (ATTRaCT) and Canadian (Alberta HEART) datasets (n=142) with repeated independent measurements by two expert sonographers.

FINDINGS

In the ATTRaCT test set, the automated workflow classified 2D videos and Doppler modalities with accuracies (number of correct predictions divided by the total number of predictions) ranging from 0·91 to 0·99. Segmentations of the left ventricle and left atrium were accurate, with a mean Dice similarity coefficient greater than 93% for all. In the external datasets (n=1029 to 10 030 echocardiograms used as input), automated measurements showed good agreement with locally measured values, with a mean absolute error range of 9-25 mL for left ventricular volumes, 6-10% for left ventricular ejection fraction (LVEF), and 1·8-2·2 for the ratio of the mitral inflow E wave to the tissue Doppler e' wave (E/e' ratio); and reliably classified systolic dysfunction (LVEF <40%, area under the receiver operating characteristic curve [AUC] range 0·90-0·92) and diastolic dysfunction (E/e' ratio ≥13, AUC range 0·91-0·91), with narrow 95% CIs for AUC values. Independent prospective evaluation confirmed less variance of automated compared with human expert measurements, with all individual equivalence coefficients being less than 0 for all measurements.

INTERPRETATION

Deep learning algorithms can automatically annotate 2D videos and Doppler modalities with similar accuracy to manual measurements by expert sonographers. Use of an automated workflow might accelerate access, improve quality, and reduce costs in diagnosing and managing heart failure globally.

FUNDING

A*STAR Biomedical Research Council and A*STAR Exploit Technologies.

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.

Structural modelling of the lumenal domain of human GPAA1, the metallo-peptide synthetase subunit of the transamidase complex, reveals zinc-binding mode and two flaps surrounding the active site

Background

The transamidase complex is a molecular machine in the endoplasmic reticulum of eukaryotes that attaches a glycosylphosphatidylinositol (GPI) lipid anchor to substrate proteins after cleaving a C-terminal propeptide with a defined sequence signal. Its five subunits are very hydrophobic; thus, solubility, heterologous expression and complex reconstruction are difficult. Therefore, theoretical approaches are currently the main source of insight into details of 3D structure and of the catalytic process.

Results

In this work, we generated model 3D structures of the lumenal domain of human GPAA1, the M28-type metallo-peptide-synthetase subunit of the transamidase, including zinc ion and model substrate positions. In comparative molecular dynamics (MD) simulations of M28-type structures and our GPAA1 models, we estimated the metal ion binding energies with evolutionary conserved amino acid residues in the catalytic cleft. We find that canonical zinc binding sites 2 and 3 are strongest binders for Zn1 and, where a second zinc is available, sites 2 and 4 for Zn2. Zinc interaction of site 5 with Zn1 enhances upon substrate binding in structures with only one zinc. Whereas a previously studied glutaminyl cyclase structure, the best known homologue to GPAA1, binds only one zinc ion at the catalytic site, GPAA1 can sterically accommodate two. The M28-type metallopeptidases segregate into two independent branches with regard to one/two zinc ion binding modality in a phylogenetic tree where the GPAA1 family is closer to the joint origin of both groups. For GPAA1 models, MD studies revealed two large loops (flaps) surrounding the active site being involved in an anti-correlated, breathing-like dynamics.

Conclusions

In the light of combined sequence-analytic and phylogenetic arguments as well as 3D structural modelling results, GPAA1 is most likely a single zinc ion metallopeptidase. Two large flaps environ the catalytic site restricting access to large substrates.

Reviewers

This article was reviewed by Thomas Dandekar (MD) and Michael Gromiha.

AllerCatPro-prediction of protein allergenicity potential from the protein sequence

Motivation

Due to the risk of inducing an immediate Type I (IgE-mediated) allergic response, proteins intended for use in consumer products must be investigated for their allergenic potential before introduction into the marketplace. The FAO/WHO guidelines for computational assessment of allergenic potential of proteins based on short peptide hits and linear sequence window identity thresholds misclassify many proteins as allergens.

Results

We developed AllerCatPro which predicts the allergenic potential of proteins based on similarity of their 3D protein structure as well as their amino acid sequence compared with a data set of known protein allergens comprising of 4180 unique allergenic protein sequences derived from the union of the major databases Food Allergy Research and Resource Program, Comprehensive Protein Allergen Resource, WHO/International Union of Immunological Societies, UniProtKB and Allergome. We extended the hexamer hit rule by removing peptides with high probability of random occurrence measured by sequence entropy as well as requiring 3 or more hexamer hits consistent with natural linear epitope patterns in known allergens. This is complemented with a Gluten-like repeat pattern detection. We also switched from a linear sequence window similarity to a B-cell epitope-like 3D surface similarity window which became possible through extensive 3D structure modeling covering the majority (74%) of allergens. In case no structure similarity is found, the decision workflow reverts to the old linear sequence window rule. The overall accuracy of AllerCatPro is 84% compared with other current methods which range from 51 to 73%. Both the FAO/WHO rules and AllerCatPro achieve highest sensitivity but AllerCatPro provides a 37-fold increase in specificity.

Availability and implementation

https://allercatpro.bii.a-star.edu.sg/

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Knockout of the non-essential gene SUGCT creates diet-linked, age-related microbiome disbalance with a diabetes-like metabolic syndrome phenotype

SUGCT (C7orf10) is a mitochondrial enzyme that synthesizes glutaryl-CoA from glutarate in tryptophan and lysine catabolism, but it has not been studied in vivo. Although mutations in Sugct lead to Glutaric Aciduria Type 3 disease in humans, patients remain largely asymptomatic despite high levels of glutarate in the urine. To study the disease mechanism, we generated SugctKO mice and uncovered imbalanced lipid and acylcarnitine metabolism in kidney in addition to changes in the gut microbiome. After SugctKO mice were treated with antibiotics, metabolites were comparable to WT, indicating that the microbiome affects metabolism in SugctKO mice. SUGCT loss of function contributes to gut microbiota dysbiosis, leading to age-dependent pathological changes in kidney, liver, and adipose tissue. This is associated with an obesity-related phenotype that is accompanied by lipid accumulation in kidney and liver, as well as “crown-like” structures in adipocytes. Furthermore, we show that the SugctKO kidney pathology is accelerated and exacerbated by a high-lysine diet. Our study highlights the importance of non-essential genes with no readily detectable early phenotype, but with substantial contributions to the development of age-related pathologies, which result from an interplay between genetic background, microbiome, and diet in the health of mammals.

Effect of the additional cysteine 503 of vancomycin-resistant Enterococcus faecalis (V583) alkylhydroperoxide reductase subunit F (AhpF) and the mechanism of AhpF and subunit C assembling

The vancomycin-resistant Enterococcus faecalis alkyl hydroperoxide reductase complex (AhpR) with its subunits AhpC (EfAhpC) and AhpF (EfAhpF) is of paramount importance to restore redox homeostasis. Therefore, knowledge about this defense system is essential to understand its antibiotic-resistance and survival in hosts. Recently, we described the crystallographic structures of EfAhpC, the two-fold thioredoxin-like domain of EfAhpF, the novel phenomenon of swapping of the catalytic domains of EfAhpF as well as the unique linker length, connecting the catalytically active N-and C-terminal domains of EfAhpF. Here, using mutagenesis and enzymatic studies, we reveal the effect of an additional third cysteine (C503) in EfAhpF, which might optimize the functional adaptation of the E. faecalis enzyme under various physiological conditions. The crystal structure and solution NMR data of the engineered C503A mutant of the thioredoxin-like domain of EfAhpF were used to describe alterations in the environment of the additional cysteine residue during modulation of the redox-state. To glean insight into the epitope and mechanism of EfAhpF and -AhpC interaction as well as the electron transfer from the thioredoxin-like domain of EfAhpF to AhpC, NMR-titration experiments were performed, showing a coordinated disappearance of peaks in the thioredoxin-like domain of EfAhpF in the presence of full length EfAhpC, and indicating a stable EfAhpF-AhpC-complex. Combined with docking studies, the interacting residues of EfAhpF were identified and a mechanism of electron transfer of the EfAhpF donor to the electron acceptor EfAhpC is described.

Hypocrisy Around Medical Patient Data: Issues of Access for Biomedical Research, Data Quality, Usefulness for the Purpose and Omics Data as Game Changer

Whether due to simplicity or hypocrisy, the question of access to patient data for biomedical research is widely seen in the public discourse only from the angle of patient privacy. At the same time, the desire to live and to live without disability is of much higher value to the patients. This goal can only be achieved by extracting research insight from patient data in addition to working on model organisms, something that is well understood by many patients. Yet, most biomedical researchers working outside of clinics and hospitals are denied access to patient records when, at the same time, clinicians who guard the patient data are not optimally prepared for the data’s analysis. Medical data collection is a time- and cost-intensive process that is most of all tedious, with few elements of intellectual and emotional satisfaction on its own. In this process, clinicians and bioinformaticians, each group with their own interests, have to join forces with the goal to generate medical data sets both from clinical trials and from routinely collected electronic health records that are, as much as possible, free from errors and obvious inconsistencies. The data cleansing effort as we have learned during curation of Singaporean clinical trial data is not a trivial task. The introduction of omics and sophisticated imaging modalities into clinical practice that are only partially interpreted in terms of diagnosis and therapy with today’s level of knowledge warrant the creation of clinical databases with full patient history. This opens up opportunities for re-analyses and cross-trial studies at future time points with more sophisticated analyses of the same data, the collection of which is very expensive.

Genomics-driven discovery of a biosynthetic gene cluster required for the synthesis of BII-Rafflesfungin from the fungus Phoma sp. F3723

Background

Phomafungin is a recently reported broad spectrum antifungal compound but its biosynthetic pathway is unknown. We combed publicly available Phoma genomes but failed to find any putative biosynthetic gene cluster that could account for its biosynthesis.

Results

Therefore, we sequenced the genome of one of our Phoma strains (F3723) previously identified as having antifungal activity in a high-throughput screen. We found a biosynthetic gene cluster that was predicted to synthesize a cyclic lipodepsipeptide that differs in the amino acid composition compared to Phomafungin. Antifungal activity guided isolation yielded a new compound, BII-Rafflesfungin, the structure of which was determined.

Conclusions

We describe the NRPS-t1PKS cluster ‘BIIRfg’ compatible with the synthesis of the cyclic lipodepsipeptide BII-Rafflesfungin [HMHDA-L-Ala-L-Glu-L-Asn-L-Ser-L-Ser-D-Ser-D-allo-Thr-Gly]. We report new Stachelhaus codes for Ala, Glu, Asn, Ser, Thr, and Gly. We propose a mechanism for BII-Rafflesfungin biosynthesis, which involves the formation of the lipid part by BIIRfg_PKS followed by activation and transfer of the lipid chain by a predicted AMP-ligase on to the first PCP domain of the BIIRfg_NRPS gene.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5762-6) contains supplementary material, which is available to authorized users.

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.

Darkness in the Human Gene and Protein Function Space: Widely Modest or Absent Illumination by the Life Science Literature and the Trend for Fewer Protein Function Discoveries Since 2000

The mentioning of gene names in the body of the scientific literature 1901-2017 and their fractional counting is used as a proxy to assess the level of biological function discovery. A literature score of one has been defined as full publication equivalent (FPE), the amount of literature necessary to achieve one publication solely dedicated to a gene. It has been found that less than 5000 human genes have each at least 100 FPEs in the available literature corpus. This group of elite genes (4817 protein-coding genes, 119 non-coding RNAs) attracts the overwhelming majority of the scientific literature about genes. Yet, thousands of proteins have never been mentioned at all, ≈2000 further proteins have not even one FPE of literature and, for ≈4600 additional proteins, the FPE count is below 10. The protein function discovery rate measured as numbers of proteins first mentioned or crossing a threshold of accumulated FPEs in a given year has grown until 2000 but is in decline thereafter. This drop is partially offset by function discoveries for non-coding RNAs. The full human genome sequencing does not boost the function discovery rate. Since 2000, the fastest growing group in the literature is that with at least 500 FPEs per gene.

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.

Function of a membrane-embedded domain evolutionarily multiplied in the GPI lipid anchor pathway proteins PIG-B, PIG-M, PIG-U, PIG-W, PIG-V, and PIG-Z

Distant homology relationships among proteins with many transmembrane regions (TMs) are difficult to detect as they are clouded by the TMs’ hydrophobic compositional bias and mutational divergence in connecting loops. In the case of several GPI lipid anchor biosynthesis pathway components, the hidden evolutionary signal can be revealed with dissectHMMER, a sequence similarity search tool focusing on fold-critical, high complexity sequence segments. We find that a sequence module with 10 TMs in PIG-W, described as acyl transferase, is homologous to PIG-U, a transamidase subunit without characterized molecular function, and to mannosyltransferases PIG-B, PIG-M, PIG-V and PIG-Z. We conclude that this new, membrane-embedded domain named BindGPILA functions as the unit for recognizing, binding and stabilizing the GPI lipid anchor in a modification-competent form as this appears the only functional aspect shared among all proteins. Thus, PIG-U's likely molecular function is shuttling/presenting the anchor in a productive conformation to the transamidase complex.

Discovering novel SNPs that are correlated with patient outcome in a Singaporean cancer patient cohort treated with gemcitabine-based chemotherapy

Background

Single Nucleotide Polymorphisms (SNPs) can influence patient outcome such as drug response and toxicity after drug intervention. The purpose of this study is to develop a systematic pathway approach to accurately and efficiently predict novel non-synonymous SNPs (nsSNPs) that could be causative to gemcitabine-based chemotherapy treatment outcome in Singaporean non-small cell lung cancer (NSCLC) patients.

Methods

Using a pathway approach that incorporates comprehensive protein-protein interaction data to systematically extend the gemcitabine pharmacologic pathway, we identified 77 related nsSNPs, common in the Singaporean population. After that, we used five computational criteria to prioritize the SNPs based on their importance for protein function. We specifically selected and screened six candidate SNPs in a patient cohort with NSCLC treated with gemcitabine-based chemotherapy.

Result

We performed survival analysis followed by hematologic toxicity analyses and found that three of six candidate SNPs are significantly correlated with the patient outcome (P < 0.05) i.e. ABCG2 Q141K (rs2231142), SLC29A3 S158F (rs780668) and POLR2A N764K (rs2228130).

Conclusions

Our computational SNP candidate enrichment workflow approach was able to identify several high confidence biomarkers predictive for personalized drug treatment outcome while providing a rationale for a molecular mechanism of the SNP effect.

Trial registration

NCT00695994. Registered 10 June, 2008 ‘retrospectively registered’.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4471-x) contains supplementary material, which is available to authorized users.

Active site CP-loop dynamics modulate substrate binding, catalysis, oligomerization, stability, over-oxidation and recycling of 2-Cys Peroxiredoxins

Peroxiredoxins (Prxs) catalyse the rapid reduction of hydrogen peroxide, organic hydroperoxide and peroxynitrite, using a fully conserved peroxidatic cysteine (C_P) located in a conserved sequence Pxxx(T/S)xxC_P motif known as C_P-loop. In addition, Prxs are involved in cellular signaling pathways and regulate several redox-dependent process related disease. The effective catalysis of Prxs is associated with alterations in the C_P-loop between reduced, Fully Folded (FF), and oxidized, Locally Unfolded (LU) conformations, which are linked to dramatic changes in the oligomeric structure. Despite many studies, little is known about the precise structural and dynamic roles of the C_P-loop on Prxs functions. Herein, the comprehensive biochemical and biophysical studies on Escherichia coli alkyl hydroperoxide reductase subunit C (EcAhpC) and the C_P-loop mutants, EcAhpC-F45A and EcAhpC-F45P reveal that the reduced form of the C_P-loop adopts conformational dynamics, which is essential for effective peroxide reduction. Furthermore, the point mutants alter the structure and dynamics of the reduced form of the C_P-loop and, thereby, affect substrate binding, catalysis, oligomerization, stability and overoxidiation. In the oxidized form, due to restricted C_P-loop dynamics, the EcAhpC-F45P mutant favours a decamer formation, which enhances the effective recycling by physiological reductases compared to wild-type EcAhpC. In addition, the study reveals that residue F45 increases the specificity of Prxs-reductase interactions. Based on these studies, we propose an evolution of the C_P-loop with confined sequence conservation within Prxs subfamilies that might optimize the functional adaptation of Prxs into various physiological roles.

Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis

BACKGROUND

Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip's law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically under the conditions of infinite observations, real world observations are finite where the finite-size effects will set in to force a power-law distribution into an exponential decay and consequently, manifests as a curvature (i.e., varying exponent values) in a log-log plot. If transcript abundance is truly power-law distributed, the varying exponent signifies changing mathematical moments (e.g., mean, variance) and creates heteroskedasticity which compromises statistical rigor in analysis. The impact of this deviation from the asymptotic power-law on sequencing count data has never truly been examined and quantified.

RESULTS

The anecdotal description of transcript abundance being almost Zipf's law-like distributed can be conceptualized as the imperfect mathematical rendition of the Pareto power-law distribution when subjected to the finite-size effects in the real world; This is regardless of the advancement in sequencing technology since sampling is finite in practice. Our conceptualization agrees well with our empirical analysis of two modern day NGS (Next-generation sequencing) datasets: an in-house generated dilution miRNA study of two gastric cancer cell lines (NUGC3 and AGS) and a publicly available spike-in miRNA data; Firstly, the finite-size effects causes the deviations of sequencing count data from Zipf's law and issues of reproducibility in sequencing experiments. Secondly, it manifests as heteroskedasticity among experimental replicates to bring about statistical woes. Surprisingly, a straightforward power-law correction that restores the distribution distortion to a single exponent value can dramatically reduce data heteroskedasticity to invoke an instant increase in signal-to-noise ratio by 50% and the statistical/detection sensitivity by as high as 30% regardless of the downstream mapping and normalization methods. Most importantly, the power-law correction improves concordance in significant calls among different normalization methods of a data series averagely by 22%. When presented with a higher sequence depth (4 times difference), the improvement in concordance is asymmetrical (32% for the higher sequencing depth instance versus 13% for the lower instance) and demonstrates that the simple power-law correction can increase significant detection with higher sequencing depths. Finally, the correction dramatically enhances the statistical conclusions and eludes the metastasis potential of the NUGC3 cell line against AGS of our dilution analysis.

CONCLUSIONS

The finite-size effects due to undersampling generally plagues transcript count data with reproducibility issues but can be minimized through a simple power-law correction of the count distribution. This distribution correction has direct implication on the biological interpretation of the study and the rigor of the scientific findings.

REVIEWERS

This article was reviewed by Oliviero Carugo, Thomas Dandekar and Sandor Pongor.

Charged residues next to transmembrane regions revisited: "Positive-inside rule" is complemented by the "negative inside depletion/outside enrichment rule"

Background

Transmembrane helices (TMHs) frequently occur amongst protein architectures as means for proteins to attach to or embed into biological membranes. Physical constraints such as the membrane’s hydrophobicity and electrostatic potential apply uniform requirements to TMHs and their flanking regions; consequently, they are mirrored in their sequence patterns (in addition to TMHs being a span of generally hydrophobic residues) on top of variations enforced by the specific protein’s biological functions.

Results

With statistics derived from a large body of protein sequences, we demonstrate that, in addition to the positive charge preference at the cytoplasmic inside (positive-inside rule), negatively charged residues preferentially occur or are even enriched at the non-cytoplasmic flank or, at least, they are suppressed at the cytoplasmic flank (negative-not-inside/negative-outside (NNI/NO) rule). As negative residues are generally rare within or near TMHs, the statistical significance is sensitive with regard to details of TMH alignment and residue frequency normalisation and also to dataset size; therefore, this trend was obscured in previous work. We observe variations amongst taxa as well as for organelles along the secretory pathway. The effect is most pronounced for TMHs from single-pass transmembrane (bitopic) proteins compared to those with multiple TMHs (polytopic proteins) and especially for the class of simple TMHs that evolved for the sole role as membrane anchors.

Conclusions

The charged-residue flank bias is only one of the TMH sequence features with a role in the anchorage mechanisms, others apparently being the leucine intra-helix propensity skew towards the cytoplasmic side, tryptophan flanking as well as the cysteine and tyrosine inside preference. These observations will stimulate new prediction methods for TMHs and protein topology from a sequence as well as new engineering designs for artificial membrane proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-017-0404-4) contains supplementary material, which is available to authorized users.

Benchmarking selected computational gene network growing tools in context of virus-host interactions

Several available online tools provide network growing functions where an algorithm utilizing different data sources suggests additional genes/proteins that should connect an input gene set into functionally meaningful networks. Using the well-studied system of influenza host interactions, we compare the network growing function of two free tools GeneMANIA and STRING and the commercial IPA for their performance of recovering known influenza A virus host factors previously identified from siRNA screens. The result showed that given small (~30 genes) or medium (~150 genes) input sets all three network growing tools detect significantly more known host factors than random human genes with STRING overall performing strongest. Extending the networks with all the three tools significantly improved the detection of GO biological processes of known host factors compared to not growing networks. Interestingly, the rate of identification of true host factors using computational network growing is equal or better to doing another experimental siRNA screening study which could also be true and applied to other biological pathways/processes.

Essential role of the flexible linker on the conformational equilibrium of bacterial peroxiredoxin reductase for effective regeneration of peroxiredoxin

Reactive oxygen species (ROS) can damage DNA, proteins, and lipids, so cells have antioxidant systems that regulate ROS. In many bacteria, a dedicated peroxiredoxin reductase, alkyl hydroperoxide reductase subunit F (AhpF), catalyzes the rapid reduction of the redox-active disulfide center of the antioxidant protein peroxiredoxin (AhpC) to detoxify ROS such as hydrogen peroxide, organic hydroperoxide, and peroxynitrite. AhpF is a flexible multidomain protein that enables a series of electron transfers among the redox centers by accepting reducing equivalents from NADH. A flexible linker connecting the N-terminal domain (NTD) and C-terminal domain (CTD) of AhpF suggests that the enzyme adopts a large-scale domain motion that alternates between the closed and open states to shuttle electrons from the CTD via the NTD to AhpC. Here, we conducted comprehensive mutational, biochemical, and biophysical analyses to gain insights into the role of the flexible linker and the residues critical for the domain motions of Escherichia coli AhpF (EcAhpF) during electron transfer. Small-angle X-ray scattering studies of linker mutants revealed that a group of charged residues, ²⁰⁰EKR²⁰², is crucial for the swiveling motion of the NTD. Moreover, NADH binding significantly affected EcAhpF flexibility and the movement of the NTD relative to the CTD. The mutants also exhibited a decrease in H₂O₂ reduction by the AhpF-AhpC ensemble. We propose that a concerted movement involving the NTD, C-terminal NADH, and FAD domains, and the flexible linker between them is essential for optimal intra-domain cross-talk and for efficient electron transfer to the redox partner AhpC required for peroxidation.

Discovery of a novel splice variant of Fcar (CD89) unravels sequence segments necessary for efficient secretion: A story of bad signal peptides and good ones that nevertheless do not make it

The IgA receptor, Fcar (CD89) consists of 5 sequence segments: 2 segments (S1, S2) forming the potential signal peptide, 2 extracellular EC domains that include the IgA binding site, and the transmembrane and cytoplasmic tail (TM/C) region. Numerous Fcar splice variants have been reported with various combinations of the sequence segments mentioned above. Here, we report a novel splice variant termed variant APD isolated from a healthy volunteer that lacks only the IgA-binding EC1 domain. Despite possessing the complete signal peptide S1+S2, the variant APD is only found in the intracellular space whereas the wild-type variant 1 is efficiently secreted and variant 4 leaks to the extracellular space. Further mutational experiments involving signal peptide replacements, cleavage site modifications, and studies on alternative isoforms demonstrate that despite the completeness of the signal peptide motif, the presence of the EC1 domain is essential for efficient extracellular export.

Toward Allosterically Increased Catalytic Activity of Insulin-Degrading Enzyme against Amyloid Peptides

The physiological role of insulin-degrading enzyme (IDE) in the intracytosolic clearance of amyloid β (Aβ) and other amyloid-like peptides supports a hypothesis that human IDE hyperactivation could be therapeutically beneficial for the treatment of late-onset Alzheimer's disease (AD). The major challenge standing in the way of this goal is increasing the specific catalytic activity of IDE against the Aβ substrate. There were previous indications that the allosteric mode of IDE activity regulation could potentially provide a highly specific path toward degradation of amyloid-like peptides, while not dramatically affecting activity against other substrates. Recently developed theoretical concepts are used here to explore potential allosteric modulation of the IDE activity as a result of single-residue mutations. Five candidates are selected for experimental follow-up and allosteric free energy calculations: Ser137Ala, Lys396Ala, Asp426Ala, Phe807Ala, and Lys898Ala. Our experiments show that three mutations (Ser137Ala, Phe807Ala, and Lys898Ala) decrease the K_m of the Aβ substrate. Mutation Lys898Ala results in increased catalytic activity of IDE; on the other hand, Lys364Ala does not change the activity and Asp426Ala diminishes it. Quantifying effects of mutations in terms of allosteric free energy, we show that favorable mutations lead to stabilization of the catalytic sites and other function-relevant distal sites as well as increased dynamics of the IDE-N and IDE-C halves that allow efficient substrate entrance and cleavage. A possibility for intramolecular upregulation of IDE activity against amyloid peptides via allosteric mutations calls for further investigations in this direction. Ultimately, we are hopeful it will lead to the development of IDE-based drugs for the treatment of the late-onset form of AD characterized by an overall impairment of Aβ clearance.

xHMMER3x2: Utilizing HMMER3's speed and HMMER2's sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation

BACKGROUND

While the local-mode HMMER3 is notable for its massive speed improvement, the slower glocal-mode HMMER2 is more exact for domain annotation by enforcing full domain-to-sequence alignments. Since a unit of domain necessarily implies a unit of function, local-mode HMMER3 alone remains insufficient for precise function annotation tasks. In addition, the incomparable E-values for the same domain model by different HMMER builds create difficulty when checking for domain annotation consistency on a large-scale basis.

RESULTS

In this work, both the speed of HMMER3 and glocal-mode alignment of HMMER2 are combined within the xHMMER3x2 framework for tackling the large-scale domain annotation task. Briefly, HMMER3 is utilized for initial domain detection so that HMMER2 can subsequently perform the glocal-mode, sequence-to-full-domain alignments for the detected HMMER3 hits. An E-value calibration procedure is required to ensure that the search space by HMMER2 is sufficiently replicated by HMMER3. We find that the latter is straightforwardly possible for ~80% of the models in the Pfam domain library (release 29). However in the case of the remaining ~20% of HMMER3 domain models, the respective HMMER2 counterparts are more sensitive. Thus, HMMER3 searches alone are insufficient to ensure sensitivity and a HMMER2-based search needs to be initiated. When tested on the set of UniProt human sequences, xHMMER3x2 can be configured to be between 7× and 201× faster than HMMER2, but with descending domain detection sensitivity from 99.8 to 95.7% with respect to HMMER2 alone; HMMER3's sensitivity was 95.7%. At extremes, xHMMER3x2 is either the slow glocal-mode HMMER2 or the fast HMMER3 with glocal-mode. Finally, the E-values to false-positive rates (FPR) mapping by xHMMER3x2 allows E-values of different model builds to be compared, so that any annotation discrepancies in a large-scale annotation exercise can be flagged for further examination by dissectHMMER.

CONCLUSION

The xHMMER3x2 workflow allows large-scale domain annotation speed to be drastically improved over HMMER2 without compromising for domain-detection with regard to sensitivity and sequence-to-domain alignment incompleteness. The xHMMER3x2 code and its webserver (for Pfam release 27, 28 and 29) are freely available at http://xhmmer3x2.bii.a-star.edu.sg/ .

REVIEWERS

Reviewed by Thomas Dandekar, L. Aravind, Oliviero Carugo and Shamil Sunyaev. For the full reviews, please go to the Reviewers' comments section.

Transition steps in peroxide reduction and a molecular switch for peroxide robustness of prokaryotic peroxiredoxins

In addition to their antioxidant function, the eukaryotic peroxiredoxins (Prxs) facilitate peroxide-mediated signaling by undergoing controlled inactivation by peroxide-driven over-oxidation. In general, the bacterial enzyme lacks this controlled inactivation mechanism, making it more resistant to high H₂O₂ concentrations. During peroxide reduction, the active site alternates between reduced, fully folded (FF), and oxidized, locally unfolded (LU) conformations. Here we present novel insights into the divergence of bacterial and human Prxs in robustness and sensitivity to inactivation, respectively. Structural details provide new insights into sub-steps during the catalysis of peroxide reduction, enabling the transition from an FF to a LU conformation. Complementary to mutational and enzymatic results, these data unravel the essential role of the C-terminal tail of bacterial Prxs to act as a molecular switch, mediating the transition from an FF to a LU state. In addition, we propose that the C-terminal tail has influence on the propensity of the disulphide bond formation, indicating that as a consequence on the robustness and sensitivity to over-oxidation. Finally, a physical linkage between the catalytic site, the C-terminal tail and the oligomer interface is described.

Protein function machinery: from basic structural units to modulation of activity

Contemporary protein structure is a result of the trade off between the laws of physics and the evolutionary selection. The polymer nature of proteins played a decisive role in establishing the basic structural and functional units of soluble proteins. We discuss how these elementary building blocks work in the hierarchy of protein domain structure, co-translational folding, as well as in enzymatic activity and molecular interactions. Next, we consider modulators of the protein function, such as intermolecular interactions, disorder-to-order transitions, and allosteric signaling, acting via interference with the protein's structural dynamics. We also discuss the post-translational modifications, which is a complementary intricate mechanism evolved for regulation of protein functions and interactions. In conclusion, we assess an anticipated contribution of discussed topics to the future advancements in the field.

A Reversible Association between Smc Coiled Coils Is Regulated by Lysine Acetylation and Is Required for Cohesin Association with the DNA

Cohesin is a ring-shaped protein complex that is capable of embracing DNA. Most of the ring circumference is comprised of the anti-parallel intramolecular coiled coils of the Smc1 and Smc3 proteins, which connect globular head and hinge domains. Smc coiled coil arms contain multiple acetylated and ubiquitylated lysines. To investigate the role of these modifications, we substituted lysines for arginines to mimic the unmodified state and uncovered genetic interaction between the Smc arms. Using scanning force microscopy, we show that wild-type Smc arms associate with each other when the complex is not on DNA. Deacetylation of the Smc1/Smc3 dimers promotes arms' dissociation. Smc arginine mutants display loose packing of the Smc arms and, although they dimerize at the hinges, fail to connect the heads and associate with the DNA. Our findings highlight the importance of a "collapsed ring," or "rod," conformation of cohesin for its loading on the chromosomes.