Phylogenetic analysis of Cryptosporidium isolates from captive reptiles using 18S rDNA sequence data and random amplified polymorphic DNA analys

Sequence alignment of a polymerase chain reaction-amplified 713-base pair region of the Cryptosporidium 18S rDNA gene was carried out on 15 captive reptile isolates from different geographic locations and compared to both Cryptosporidium parvum and Cryptosporidium muris isolates. Random amplified polymorphic DNA (RAPD) analysis was also performed on a smaller number of these samples. The data generated by both techniques were significantly correlated (P < 0.002), providing additional evidence to support the clonal population structure hypothesis for Cryptosporidium. Phylogenetic analysis of both 18S sequence information and RAPD analysis grouped the majority of reptile isolates together into 1 main group attributed to Cryptosporidium serpentis, which was genetically distinct but closely related to C. muris. A second genotype exhibited by 1 reptile isolate (S6) appeared to be intermediate between C. serpentis and C. muris but grouped most closely with C. muris, as it exhibited 99.15% similarity with C. muris and only 97.13% similarity with C. serpentis. The third genotype identified in 2 reptile isolates was a previously characterized 'mouse' genotype that grouped closely with bovine and human C. parvum isolates

Molecular and phylogenetic analysis of Cryptosporidium muris from various hosts

Isolates of Cryptosporidium muris and C. serpentis were characterized from different hosts using nucleotide sequence analysis of the rDNA 18S and ITS1 regions, and the heat-shock (HSP-70) gene. Phylogenetic analysis confirmed preliminary evidence that C. muris is not a uniform species. Two distinct genotypes were identified within C. muris; (1) C. muris genotype A; comprising bovine and camel isolates of C. muris from different geographical locations, and (2) C. muris genotype B comprising C. muris isolates from mice, a hamster, a rock hyrax and a camel from the same enclosure. These 2 genotypes may represent separate species but further biological and molecular studies are required for confirmation

Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution

Various lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have contributed to prolongation of the coronavirus disease 2019 (COVID-19) pandemic. Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least five hundred in each SARS-CoV-2 protein; we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frames (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. Characterization of the periodically aperiodic nature of the demographic spread of SARS-CoV-2 variants in various countries can contribute to the identification of the origin of SARS-CoV-2

Implications derived from S-protein variants of SARS-CoV-2 from six continents

Spike (S) protein is a critical determinant of the infectivity and antigenicity of SARS-CoV-2. Several mutations in the spike protein of SARS-CoV-2 have already been detected, and their effect in immune system evasion and enhanced transmission as a cause of increased morbidity and mortality are being investigated. From pathogenic and epidemiological perspectives, spike proteins are of prime interest to researchers. This study focused on the unique variants of S proteins from six continents: Asia, Africa, Europe, Oceania, South America, and North America. In comparison to the other five continents, Africa had the highest percentage of unique S proteins (29.1%). The phylogenetic relationship implies that unique S proteins from North America are significantly different from those of the other five continents. They are most likely to spread to the other geographic locations through international travel or naturally by emerging mutations. It is suggested that restriction of international travel should be considered, and massive vaccination as an utmost measure to combat the spread of COVID-19 pandemic. It is also further suggested that the efficacy of existing vaccines and future vaccine development must be reviewed with careful scrutiny, and if needed, further re-engineered based on requirements dictated by new emerging S protein variants

An issue of concern: unique truncated ORF8 protein variants of SARS-CoV-2

Open reading frame 8 (ORF8) shows one of the highest levels of variability among accessory proteins in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19). It was previously reported that the ORF8 protein inhibits the presentation of viral antigens by the major histocompatibility complex class I (MHC-I), which interacts with host factors involved in pulmonary inflammation. The ORF8 protein assists SARS-CoV-2 in evading immunity and plays a role in SARS-CoV-2 replication. Among many contributing mutations, Q27STOP, a mutation in the ORF8 protein, defines the B.1.1.7 lineage of SARS-CoV-2, engendering the second wave of COVID-19. In the present study, 47 unique truncated ORF8 proteins (T-ORF8) with the Q27STOP mutations were identified among 49,055 available B.1.1.7 SARS-CoV-2 sequences. The results show that only one of the 47 T-ORF8 variants spread to over 57 geo-locations in North America, and other continents, which include Africa, Asia, Europe and South America. Based on various quantitative features, such as amino acid homology, polar/non-polar sequence homology, Shannon entropy conservation, and other physicochemical properties of all specific 47 T-ORF8 protein variants, nine possible T-ORF8 unique variants were defined. The question as to whether T-ORF8 variants function similarly to the wild type ORF8 is yet to be investigated. A positive response to the question could exacerbate future COVID-19 waves, necessitating severe containment measures

Glycan biomarkers of autoimmunity and bile acid-associated alterations of the human glycome: primary biliary cirrhosis and primary sclerosing cholangitis-specific glycans

We have recently introduced multiple reaction monitoring (MRM) mass spectrometry as a novel tool for glycan biomarker research and discovery. Herein, we employ this technique to characterize the site-specific glycan alterations associated with primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Glycopeptides associated with disease severity were also identified. Multinomial regression modelling was employed to construct and validate multi-analyte diagnostic models capable of accurately distinguishing PBC, PSC, and healthy controls from one another (AUC = 0.93 +/- 0.03). Finally, to investigate how disease-relevant environmental factors can influence glycosylation, we characterized the ability of bile acids known to be differentially expressed in PBC to alter glycosylation. We hypothesize that this could be a mechanism by which altered selfantigens are generated and become targets for immune attack. This work demonstrates the utility of the MRM method to identify diagnostic site-specific glycan classifiers capable of distinguishing even related autoimmune diseases from one another.Afdeling Klinische Chemie en Laboratoriumgeneeskunde (AKCL

Genetics of grain yield and its components in wheat under heat stress

Heat stress is a matter of a great concern for the wheat crop. Heat stress usually either hastens crop development or shortens the grain filling duration, which severely reduces grain yield. Being a complex trait, understanding the genetics and gene interactions of stress tolerance are the two primary requirements for improving yield levels. Genetic analysis through generation mean analysis helps to find out the nature of gene actions involved in a concerned trait by providing an estimate of main gene effects (additive and dominance) along with their digenic interactions (additive × additive, additive × dominance, and dominance × dominance). In the present investigation, we elucidated the inheritance pattern of different yield contributing traits under heat stress using different cross combinations which could be helpful for selecting a suitable breeding strategy. Thus six generations of five crosses were sown normal (non-stress, TS) and late (heat stress, LS) in a randomized block design with three replications during two crop seasons. The model was not adequate for late sown conditions indicating the expression of epistatic genes under stress conditions. The traits i.e. Days to heading (DH), Days to anthesis (DA), Days to maturity (DM), Grain filling duration (GFD), Grain yield (GY), Thousand grain weight (TGW), Grain weight per spike (GWS) and Heat susceptibility index (HSI) under heat stress conditions were found under the control of additive gene action with dominance × dominance interaction, additive gene action with additive × dominance epistatic effect, dominance gene action with additive × additive interaction effect, additive and dominance gene action with dominance × dominance interaction effect, additive gene action with additive × dominance epistatic effect, additive gene action with additive × additive interaction effect and dominance gene action with additive × additive interaction effect, respectively