Classification and characterization of multigene family proteins of African swine fever viruses

African swine fever virus (ASFV) poses serious threats to the pig industry. The multigene family (MGF) proteins are extensively distributed in ASFVs and are generally classified into five families, including MGF-100, MGF-110, MGF-300, MGF-360 and MGF-505. Most MGF proteins, however, have not been well characterized and classified within each family. To bridge this gap, this study first classified MGF proteins into 31 groups based on protein sequence homology and network clustering. A web server for classifying MGF proteins was established and kept available for free at http://www.computationalbiology.cn/MGF/home.html. Results showed that MGF groups of the same family were most similar to each other and had conserved sequence motifs; the genetic diversity of MGF groups varied widely, mainly due to the occurrence of indels. In addition, the MGF proteins were predicted to have large structural and functional diversity, and MGF proteins of the same MGF family tended to have similar structure, location and function. Reconstruction of the ancestral states of MGF groups along the ASFV phylogeny showed that most MGF groups experienced either the copy number variations or the gain-or-loss changes, and most of these changes happened within strains of the same genotype. It is found that the copy number decrease and the loss of MGF groups were much larger than the copy number increase and the gain of MGF groups, respectively, suggesting the ASFV tended to lose MGF proteins in the evolution. Overall, the work provides a detailed classification for MGF proteins and would facilitate further research on MGF proteins.

Discovery of an ultra-specific triuret hydrolase (TrtA) establishes the triuret biodegradation pathway

Triuret (carbonyldiurea) is an impurity found in industrial urea fertilizer (<0.1% w/w) that is applied, worldwide, around 300 million pounds each year on agricultural lands. In addition to anthropogenic sources, endogenous triuret has been identified in amoeba and human urine, the latter being diagnostic for hypokalemia. The present study is the first to describe the metabolic breakdown of triuret, which funnels into biuret metabolism. We identified the gene responsible for triuret decomposition (trtA) in bacterial genomes, clustered with biuH, that encodes biuret hydrolase and has close protein sequence homology. TrtA is a member of the isochorismatase-like hydrolase protein family (IHL), similarly to BiuH, and has a catalytic efficiency (kcat/KM) of 6 x 105 (M-1s-1), a KM for triuret of 20 μM, and exquisite substrate specificity. Indeed, TrtA has four orders of magnitude less activity with biuret. Crystal structures of TrtA in apo and holo form were solved and compared to the BiuH structure. The high substrate selectivity was found to be conveyed by second shell residues around each active site. Mutagenesis of residues conserved in TrtA to the alternate consensus found in BiuHs revealed residues critical to triuret hydrolase activity but no single mutant evolved more biuret activity and likely a combination of mutations is required to interconvert between TrtA, BiuH functions. TrtA-mediated triuret metabolism is relatively rare in recorded genomes (1-2%), but is largely found in plant-associated, nodulating and endophytic bacteria. This study suggests functions for triuret hydrolase in certain eukaryotic intermediary processes and prokaryotic intermediary or biodegradative metabolism

Classification of multigene families of African swine fever viruses

African swine fever virus (ASFV) is a large and complex double-stranded DNA virus that poses serious threats to the pig industry. It is well-accepted that the multigene family (MGF) proteins are extensively distributed in ASFVs and are generally classified into five families, including MGF-100, MGF-110, MGF-300, MGF-360 and MGF-505. Most MGF proteins, however, have not been well characterized and classified within each family. To bridge this gap, this study first classified the MGF proteins into 35 groups based on protein sequence homology. A web server for classifying the MGF proteins was then established and available for free at http://www.computationalbiology.cn/MGF/home.html. Results showed that the genetic diversity of the MGF groups varied widely, mainly due to the occurrence of indels. In addition, the MGF proteins were predicted to have large structural and functional diversity, and the MGF proteins of the same MGF family tended to have similar structure, location and function. Evolutionary analysis revealed the dynamic changes of the MGF proteins in the ASFV genomes, and more than half of MGF groups were presented in all ASFV genomes, which indicated the important role of MGF proteins in ASFVs. Overall, it is expected that the work would not only provide a detailed classification for MGF proteins, but also facilitate further research on MGF proteins.

Fast and sensitive protein sequence homology searches using hierarchical cluster BLAST

The throughput of DNA sequencing continues to increase, allowing researchers to analyze genomes of interest at greater depths. An unintended consequence of this data deluge is the increased cost of analyzing these datasets. As a result, genome and metagenome annotation pipelines are left with a few options: (i) search against smaller reference databases, (ii) use faster, but less sensitive, algorithms to assess sequence similarities, or (iii) invest in computing hardware specifically designed to improve BLAST searches such as GPGPU systems and/or large CPU-rich clusters.We present a pipeline that improves the speed of amino acid sequence homology searches with a minimal decrease in sensitivity and specificity by searching against hierarchical clusters. Briefly, the pipeline requires two homology searches: the first search is against a clustered version of the database and the second is against sequences belonging to clusters with a hit from the first search. We tested this method using two assembled viral metagenomes and three databases (Swiss-Prot, Metagenomes Online, and UniRef100). Hierarchical cluster homology searching proved to be 12-times faster than BLASTp and produced alignments that were nearly identical to BLASTp (precision=0.99; recall=0.97). This approach is ideal when searching large collections of sequences against large databases.

Relationship between vitiligo and Hashimoto's thyroiditis

<p><strong>Background</strong>: Vitiligo is a multifactorial acquired depigmenting disorder, characterized by a spontaneous loss of functional melanocytes from the epidermis. Vitiligo and Hashimoto's thyroiditis (HT) often occur in association and seem to be characterized by an autoimmune process. The vitiligo associated with HT suggests genetic homologies between them.</p><p><strong>Objective</strong>: To identify protein sequence homology between melanocyte protein (Pmel) and thyroid peroxidase (TPO), using bioinformatics tools, to propose an initial mechanism which could explain the production of cross-reacting autoantibodies to melanocyte and TPO.</p><p><strong>Methods</strong>: We performed a comparison between Pmel and TPO amino acids (AA) sequences, available on the National Center for Biotechnology Information (NCBI) database by BLAST (Basic Local Alignment Search Tool) in order to find local homology regions between the AA sequences.</p><p><strong>Results</strong>: The homology sequence between the Pmel and TPO ranged from 21.0 % (19 identical residues out of 90 AA in the sequence) to 55.0% (6 identical residues out of 11 AA in the sequence). The identical alignments presented relatively high E values due to presence of short alignment.</p><p><strong>Conclusion</strong>: Bioinformatics data suggest a possible pathological link between Pmel and TPO. Sequence homology between Pmel and TPO may present a molecular mimicry suggesting the possibility of antigen crossover between Pmel and TPO that might represent an immunological basis for vitiligo associated with HT.</p>

The role played by drug efflux pumps in bacterial multidrug resistance

Antimicrobial resistance is a current major challenge in chemotherapy and infection control. The ability of bacterial and eukaryotic cells to recognize and pump toxic compounds from within the cell to the environment before they reach their targets is one of the important mechanisms contributing to this phenomenon. Drug efflux pumps are membrane transport proteins that require energy to export substrates and can be selective for a specific drug or poly-specific that can export multiple structurally diverse drug compounds. These proteins can be classified into seven groups based on protein sequence homology, energy source and overall structure. Extensive studies on efflux proteins have resulted in a wealth of knowledge that has made possible in-depth understanding of the structures and mechanisms of action, substrate profiles, regulation and possible inhibition of many clinically important efflux pumps. This review focuses on describing known families of drug efflux pumps using examples that are well characterized structurally and/or biochemically.

On the apparent rarity of epithelial cancers in captive chimpanzees

Malignant neoplasms arising from epithelial cells are called carcinomas. Such cancers are diagnosed in about one in three humans in ‘developed’ countries, with the most common sites affected being lung, breast, prostate, colon, ovary and pancreas. By contrast, carcinomas are said to be rare in captive chimpanzees, which share more than 99% protein sequence homology with humans (and possibly in other related ‘great apes’—bonobos, gorillas and orangutans). Simple ascertainment bias is an unlikely explanation, as these nonhuman hominids are recipients of excellent veterinary care in research facilities and zoos, and are typically subjected to necropsies when they die. In keeping with this notion, benign tumours and cancers that are less common in humans are well documented in this population. In this brief overview, we discuss other possible explanations for the reported rarity of carcinomas in our closest evolutionary cousins, including inadequacy of numbers surveyed, differences in life expectancy, diet, genetic susceptibility, immune responses or their microbiomes, and other potential environmental factors. We conclude that while relative carcinoma risk is a likely difference between humans and chimpanzees (and possibly other ‘great apes’), a more systematic survey of available data is required for validation of this claim.