Evolutionary Bioinformatics最新文献

A high level of mutation enables the influenza A virus to resist antibiotics previously effective against the influenza A virus. A portion of the structure of hemagglutinin HA is assumed to be well-conserved to maintain its role in cellular fusion, and the structure tends to be more conserved than sequence. We designed peptide inhibitors to target the conserved residues on the HA surface, which were identified based on structural alignment. Most of the conserved and strongly similar residues are located in the receptor-binding and esterase regions on the HA1 domain In a later step, fragments of anti-HA antibodies were gathered and screened for the binding ability to the found conserved residues. As a result, Methionine amino acid got the best docking score within the -2.8 Å radius of Van der Waals when it is interacting with Tyrosine, Arginine, and Glutamic acid. Then, the binding affinity and spectrum of the fragments were enhanced by grafting hotspot amino acid into the fragments to form peptide inhibitors. Our peptide inhibitor was able to form in silico contact with a structurally conserved region across H1, H2, and H3 HA, with the binding site at the boundary between HA1 and HA2 domains, spreading across different monomers, suggesting a new target for designing broad-spectrum antibody and vaccine. This research presents an affordable method to design broad-spectrum peptide inhibitors using fragments of an antibody as a scaffold.

ORF8 is a highly variable genomic region of SARS-CoV-2. Although non-essential and the precise functions are unknown, it has been suggested that this protein assists in SARS-CoV-2 replication in the early secretory pathway and in immune evasion. We utilized the binding partners of SARS-CoV-2 proteins in human HEK293T cells and performed genome-wide phylogenetic profiling and clustering analyses in 446 eukaryotic species to predict and discover ORF8 binding partners that share associated functional mechanisms based on co-evolution. Results classified 47 ORF8 binding partner proteins into 3 clusters (groups 1-3), which were conserved in vertebrates (group 1), metazoan (group 2), and eukaryotes (group 3). Gene ontology analysis indicated that group 1 had no significant associated biological processes, while groups 2 and 3 were associated with glycoprotein biosynthesis process and ubiquitin-dependent endoplasmic reticulum-associated degradation pathways, respectively. Collectively, our results classified potential genes that might be associated with SARS-CoV-2 viral pathogenesis, specifically related to acute respiratory distress syndrome, and the secretory pathway. Here, we discuss the possible role of ORF8 in viral pathogenesis and in assisting viral replication and immune evasion via secretory pathway, as well as the possible factors associated with the rapid evolution of ORF8.

Sub-Saharan Africa is courting the risk of artemisinin resistance (ARTr) emerging in Plasmodium falciparum malaria parasites. Current molecular surveillance efforts for ARTr have been built on the utility of P. falciparum kelch13 (pfk13) validated molecular markers. However, whether these molecular markers will serve the purpose of early detection of artemisinin-resistant parasites in Ghana is hinged on a pfk13 dependent evolution. Here, we tested the hypothesis that the background pfk13 genome may be present before the pfk13 ARTr-conferring variant(s) is selected and that signatures of balancing selection on these genomic loci may serve as an early warning signal of ARTr. We analyzed 12 198 single nucleotide polymorphisms (SNPs) in Ghanaian clinical isolates in the Pf3K MalariaGEN dataset that passed a stringent filtering regimen. We identified signatures of balancing selection in 2 genes (phosphatidylinositol 4-kinase and chloroquine resistance transporter) previously reported as background loci for ARTr. These genes showed statistically significant and high positive values for Tajima's D, Fu and Li's F, and Fu and Li's D. This indicates that the biodiversity required to establish a pfk13 background genome may have been primed in clinical isolates of P. falciparum from Ghana as of 2010. Despite the absence of ARTr in Ghana to date, our finding supports the current use of pfk13 for molecular surveillance of ARTr in Ghana and highlights the potential utility of monitoring malaria parasite populations for balancing selection in ARTr precursor background genes as early warning molecular signatures for the emergence of ARTr.

Wild-caught animals must cope with drastic lifestyle and dietary changes after being induced to captivity. How the gut microbiome structure of these animals will change in response receives increasing attention. The plateau zokor (Eospalax baileyi), a typic subterranean rodent endemic to the Qinghai-Tibet plateau, spends almost the whole life underground and is well adapted to the environmental pressures of both plateau and underground. However, how the gut microbiome of the plateau zokor will change in response to captivity has not been reported to date. This study compared the microbial community structure and functions of 22 plateau zokors before (the WS group) and after being kept in captivity for 15 days (the LS group, fed on carrots) using the 16S rRNA gene via high-throughput sequencing technology. The results showed that the LS group retained 973 of the 977 operational taxonomic units (OTUs) in the WS group, and no new OTUs were found in the LS group. The dominant bacterial phyla were Bacteroides and Firmicutes in both groups. In alpha diversity analysis, the Shannon, Sobs, and ACE indexes of the LS group were significantly lower than those of the WS group. A remarkable difference (P < 0.01) between groups was also detected in beta diversity analysis. The UPGMA clustering, NMDS, PCoA, and Anosim results all showed that the intergroup difference was significantly greater than the intragroup difference. And compared with the WS group, the intragroup difference of the gut microbiota in the LS group was much larger, which failed to support the assumption that similar diets should drive convergence of gut microbial communities. PICRUSt revealed that although some functional categories displayed significant differences between groups, the relative abundances of these categories were very close in both groups. Based on all the results, we conclude that as plateau zokors enter captivity for a short time, although the relative abundances of different gut microbiota categories shifted significantly, they can maintain almost all the OTUs and the functions of the gut microbiota in the wild. So, the use of wild-caught plateau zokors in gut microbial studies is acceptable if the time in captivity is short.

Hepatocellular carcinoma (HCC) is one of the common cancers with a high incidence and mortality. The human replication factor C (RFC) family contains 5 subunits that play an important role in DNA replication and DNA damage repair. RFCs are abnormally expressed in a variety of cancers; some of them are differentially expressed in HCC tissues and related to tumor growth. However, the expression, prognostic value, and effect targets of the whole RFC family in HCC are still unclear. To address these issues, we performed a multidimensional analysis of RFCs in HCC patients by Oncomine, UALCAN, GEPIA, Human protein atlas, Kaplan-Meier plotter, cBioPortal, GeneMANIA, String, and LinkedOmics. mRNA expression of RFCs was significantly increased in HCC tissues. There was a significant correlation between the expression of RFC2/3/4/5 and tumor stage of HCC patients. Besides, high mRNA expression of RFC2/4 was associated with worse overall survival (OS). Moreover, genetic alterations of RFCs were associated with worse OS in HCC patients. We found that genes co-expressed with RFC2/4 were mainly involved in biological processes, such as chromosome segregation, mitotic cell cycle phase transition, and telomere organization and they activated the cell cycle and spliceosome pathways. The gene set is mainly enriched in cancer-related kinases AURKA, ATR, CDK1, PLK1, and CHEK1. E2F family members were the key transcription factors for RFCs. Our results suggest that differentially expressed RFC2 and RFC4 are potential prognostic biomarkers in HCC and may act on E2F transcription factors and some kinase targets to dysregulate the cell cycle pathway. These efforts may provide new research directions for prognostic biomarkers and therapeutic targets in HCC.

Cycads have developed a complex root system categorized either as normal or coralloid roots. Past literatures revealed that a great diversity of key microbes is associated with these roots. This recent study aims to comprehensively determine the diversity and community structure of bacteria and fungi associated with the roots of two Cycas spp. endemic to China, Cycas debaoensis Zhong & Chen and Cycas fairylakea D.Y. Wang using high-throughput amplicon sequencing of the full-length 16S rRNA (V1-V9 hypervariable) and short fragment ITS region. The total DNA from 12 root samples were extracted, amplified, sequenced, and analyzed. Resulting sequences were clustered into 61 bacteria and 2128 fungal OTUs. Analysis of community structure revealed that the coralloid roots were dominated mostly by the nitrogen-fixer Nostocaceae but also contain other non-diazotrophic bacteria. The sequencing of entire 16S rRNA gene identified four different strains of cyanobacteria under the heterocystous genera Nostoc and Desmonostoc. Meanwhile, the top bacterial families in normal roots were Xanthobacteraceae, Burkholderiaceae, and Bacillaceae. Moreover, a diverse fungal community was also found in the roots of cycads and the predominating families were Ophiocordycipitaceae, Nectriaceae, Bionectriaceae, and Trichocomaceae. Our results demonstrated that bacterial diversity in normal roots of C. fairylakea is higher in richness and abundance than C. debaoensis. On the other hand, a slight difference, albeit insignificant, was noted for the diversity of fungi among root types and host species as the number of shared taxa is relatively high (67%). Our results suggested that diverse microbes are present in roots of cycads which potentially interact together to support cycads survival. Our study provided additional knowledge on the microbial diversity and composition in cycads and thus expanding our current knowledge on cycad-microbe association. Our study also considered the possible impact of ex situ conservation on cyanobiont community of cycads.

The SARS-CoV-2 virus that causes the COVID-19 disease has spread quickly and massively around the entire globe, causing millions of confirmed cases and deaths worldwide. The disease poses a serious ongoing threat to public health. This study aims to understand the disease potential of the virus in different regions by studying how average spring temperature and its strong predictor, latitude, affect epidemiological variables such as disease incidence, mortality, recovery cases, active cases, testing rate, and hospitalization. We also seek to understand the association of temperature and geographic coordinates with viral genomics. Epidemiological data along with temperature, latitude, longitude, and preparedness index were collected for different countries and US states during the early stages of the pandemic. Our worldwide epidemiological analysis showed a significant correlation between temperature and incidence, mortality, recovery cases and active cases. The same tendency was found with latitude, but not with longitude. In the US, we observed no correlation between temperature or latitude and epidemiological variables. Interestingly, longitude was correlated with incidence, mortality, active cases, and hospitalization. An analysis of mutational change and mutational change per time in 55 453 aligned SARS-CoV-2 genome sequences revealed these parameters were uncorrelated with temperature and geographic coordinates. The epidemiological trends we observed worldwide suggest a seasonal effect for the disease that is not directly controlled by the genomic makeup of the virus. Future studies will need to determine if correlations are more likely the result of effects associated with the environment or the innate immunity of the host.

Introns are highly variable in number and size. Sequence simulation is an effective method to elucidate intron evolution patterns. Previously, we have reported that introns are more likely to evolve through mutation-and-deletion (MD) rather than through mutation-and-insertion (MI). In the present study, we further studied evolution models by allowing insertion in the MD model and by allowing deletion in the MI model at various frequencies. It was found that all deletion-biased models with proper parameter settings could generate sequences with attributes matchable to 16 invertebrate introns from the microphthalmia transcription factor gene, whereas all insertion-biased models with any parameter settings failed to generate such sequences. We conclude that the examined invertebrate introns may have evolved from a longer ancestral sequence in a deletion-biased pattern. The constructed models are useful for studying the evolution of introns from other genes and/or from other taxonomic groups. (C++ scripts of all deletion- and insertion-biased models are available upon request.).

The study of protein self-interactions (SIPs) can not only reveal the function of proteins at the molecular level, but is also crucial to understand activities such as growth, development, differentiation, and apoptosis, providing an important theoretical basis for exploring the mechanism of major diseases. With the rapid advances in biotechnology, a large number of SIPs have been discovered. However, due to the long period and high cost inherent to biological experiments, the gap between the identification of SIPs and the accumulation of data is growing. Therefore, fast and accurate computational methods are needed to effectively predict SIPs. In this study, we designed a new method, NLPEI, for predicting SIPs based on natural language understanding theory and evolutionary information. Specifically, we first understand the protein sequence as natural language and use natural language processing algorithms to extract its features. Then, we use the Position-Specific Scoring Matrix (PSSM) to represent the evolutionary information of the protein and extract its features through the Stacked Auto-Encoder (SAE) algorithm of deep learning. Finally, we fuse the natural language features of proteins with evolutionary features and make accurate predictions by Extreme Learning Machine (ELM) classifier. In the SIPs gold standard data sets of human and yeast, NLPEI achieved 94.19% and 91.29% prediction accuracy. Compared with different classifier models, different feature models, and other existing methods, NLPEI obtained the best results. These experimental results indicated that NLPEI is an effective tool for predicting SIPs and can provide reliable candidates for biological experiments.

The adaptive evolution and coevolution of the ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (rbcL) gene in the genus Hildenbrandia were studied based on phylogenetic tree construction and the physicochemical properties and the secondary structures of protein encoded by rbcL (Rubisco large subunit) were analyzed. The amino acids compositions and grand average of hydropathicity of freshwater H. rivularis and marine H. rubra were similar. Rubisco large subunit of Hildenbrandia was hydrophilic and the secondary structure was primarily composed of α-helixes and β-sheets, revealing the relatively stable structure of this protein. The predicted phosphorylation sites in H. rivularis and H. rubra were 33 and 36, respectively. No positive selection sites were detected in the genus Hildenbrandia, implying that rbcL gene evolved either neutrally or under purifying selection. A total of 41 coevolutionary groups were detected in the Rubisco large subunit of Hildenbrandia and the coevolving sites are in closer proximity in 3-dimensional structure of the protein. Despite the long evolutionary history, rbcL gene in genus Hildenbrandia under different environments is rather conservative.