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Computational Biology and Bioinformatics in Anti-SARS-CoV-2 Drug Development
Published in Debmalya Barh, Kenneth Lundstrom, COVID-19, 2022
Phylogenetic analysis of different SARS-CoV-2 isolates allows researchers to look at the in-host evolution of this virus and to find clades – clusters of related genomes grouped according to common mutations. For example, such analysis conducted for over 5,000 SARS-CoV-2 genomes isolated from Indian COVID-19 patients produced a phylogeny with 6,888 mutation events [15]. Here, the presence of a prominent clade I/A3i, which was characterized by a set of 4 mutations and likely arose from a single outbreak, was noticed in samples retrieved during the early spread of infection. Importantly, while originally 42% of all genomes sequenced in India belonged to this clade, it evolved quickly via changes in the Nucleocapsid (N) and Membrane (M) genes, and has become almost non-existent in recent samples [15]. An integrated semi-alignment–based computational technique was utilized to analyze 2,391 genomic SARS-CoV-2 sequences to look at the SARS-CoV-2 sequence variability in human hosts from 54 different countries and to analyze sequence variability between the CoV family and country-specific SARS-CoV-2 sequences in human hosts [42].
Roots and Tubers
Published in Christopher Cumo, Ancestral Diets and Nutrition, 2020
As noted, many people confuse yams and sweet potatoes even though they are different types of angiosperms (flowering plants). For example, African American authors Richard Nathaniel Wright (1908–1960) and Ralph Waldo Ellison (1914–1994) called sweet potatoes yams, an error the USDA abetted by permitting retailers to brand Puerto Rican sweet potatoes as yams.213 Sweet potatoes are eudicots, whereas yams are monocotyledons (monocots). These clades evolved separately during roughly the past 130 million years ago.214 Despite superficial similarities to sweet potatoes, yams are more related to onion, leek, shallot (Allium ascalonicum), garlic (Allium sativum), and chives (Allium schoenoprasum), all monocots. Despite dissimilar appearances, yams are more related to wheat, rye, barley, oats, corn, and other grains because—again—all are monocots than to sweet potatoes.
Astrovirus
Published in Dongyou Liu, Handbook of Foodborne Diseases, 2018
Victoria A. Meliopoulos, Virginia Hargest, Valerie Cortez
Three distinct clades of HAstVs have been identified. The first clade includes the eight classical genotypes that were thought to be the sole causes of HAstV infections until the late 2000s, when an additional eight genotypes were identified and named after the location where they were first discovered: Melbourne (MLB 1–3) and Virginia (VA 1–5).13–19 Phylogenetic analysis revealed that MLB and VA genotypes occupy two unique clades within Mamastrovirus that are distinct from the classical genotypes. The extent to which viruses from the three clades contribute to foodborne illnesses remains unclear, largely due to limited surveillance and screening of the food supply chain for these agents.
Ampicillin-resistant and vancomycin-susceptible Enterococcus faecium bacteremia: a clinical narrative review
Published in Expert Review of Anti-infective Therapy, 2023
Daniel Echeverria-Esnal, Luisa Sorli, María Eugenia Navarrete-Rouco, Nuria Prim, Jaime Barcelo-Vidal, David Conde-Estévez, María Milagro Montero, Clara Martin-Ontiyuelo, Juan Pablo Horcajada, Santiago Grau
Within E. faecium, two types of populations are distinguishable: Clade A and Clade B [12]. Initially, most community isolates that act as commensal strains were grouped within Clade B, whilst nosocomial isolates with pathogenic potential were grouped into Clade A [6,12,13]. Clade A is divided into two subpopulations: A1 (strains isolated in humans and in hospital settings, especially) and A2 (strains isolated in animals and in out-of-hospital environments) [1]. EfARSV belongs to this clade A1. A1 strains have a larger chromosome size and a higher number of mobile genetic elements, pathogenic islands and genes for antibiotic resistance, membrane proteins, regulatory and virulence factors [12,13]. These virulence genes facilitate attachment, increased bacterial load during colonization, biofilm production and pathogenesis [13]. In terms of antibiotic resistance, a more increased resistance to ampicillin was observed in strains belonging to A1 [14]. For all these reasons, A1 is predominant in hospitals and is responsible for the rise and expansion of E. faecium infections around the world [12].
The cnf1 gene is associated with an expanding Escherichia coli ST131 H30Rx/C2 subclade and confers a competitive advantage for gut colonization
Published in Gut Microbes, 2022
Landry L. Tsoumtsa Meda, Luce Landraud, Serena Petracchini, Stéphane Descorps-Declere, Emeline Perthame, Marie-Anne Nahori, Laura Ramirez Finn, Molly A. Ingersoll, Rafael Patiño-Navarrete, Philippe Glaser, Richard Bonnet, Olivier Dussurget, Erick Denamur, Amel Mettouchi, Emmanuel Lemichez
Proportion of cnf1 along time was modeled using a generalized linear model fitted with binomial distribution and logit link. The model was adjusted on the effect of years and clades with an interaction between these two factors. We used the Tukey’s HSD test which adjusts the P-values for multiple comparisons (5 comparisons, one by clade and one for gathered clades). First, to test if the evolution of cnf1 proportion was either specific to each clade or global, the significance of the interaction term was tested with a likelihood ratio test, which compares the above-mentioned model against the null model, with no interaction. Then, we investigated the possible increase of the proportion of cnf1 within each clade. The significance of the slope coefficient for each clade was tested by computing contrasts of the above model. P-values were adjusted for multiplicity using single-step correction method. The distribution of fimH alleles and clades/subclades within the study population of E. coli ST131 was analyzed with a similar approach, except that a Poisson regression model was used to model counting data. The hypothesis testing strategy to investigate the significance of the increase of fimH alleles and clades/subclades along time is discussed above.
An update on host immunity correlates and prospects of re-infection in COVID-19
Published in International Reviews of Immunology, 2022
Neema Negi, Shesh Prakash Maurya, Ravinder Singh, Bimal Kumar Das
Emerging genetic variants could be associated with reinfections and could cause an elevation in COVID-19 cases globally. Manaus city of Brazil achieved 76% COVID-19 sero-prevalence in October 2020, but it experienced second COVID-19 wave in Dec 2020–Jan 2021 [19]. 42% of COVID-19 patients in Manaus and 51% of COVID-19 patients in Amazonas state had E484K P.1 lineage in mid Dec 2020 [171, 172] E484K P.1 lineage drastically increased to 91% in Jan 2021 in Amazonas state, and E484K spike mutation has been found in at least 3 Brazilian reinfection cases [22, 173, 174]. It may not necessarily mean that only genetic variants of SARS-CoV-2 would cause reinfection as coronaviruses, in general, are known to cause reinfection multiple times in a year [175]. These synchronic, monophyletic set of lineage-representatives have been defined as clades [176]. Although SARS-CoV-2 reinfection clade has been shown to be different in most of the reported reinfection cases but in few exceptional cases, for instance, the reinfection case from Nevada case, same clade was found in both the first and second episode of infection with a variation of 6 single nucleotides and 1 multi nucleotide in its non-spike genes [43]. Likewise, reinfection with the same SARS-CoV-2 clade has also been reported from India [177].