Enhancing Gene Co-Expression Network Inference for the Malaria Parasite Plasmodium falciparum.

BACKGROUND: Malaria results in more than 550,000 deaths each year due to drug resistance in the most lethal Plasmodium (P.) species P. falciparum. A full P. falciparum genome was published in 2002, yet 44.6% of its genes have unknown functions. Improving the functional annotation of genes is important for identifying drug targets and understanding the evolution of drug resistance. RESULTS: Genes function by interacting with one another. So, analyzing gene co-expression networks can enhance functional annotations and prioritize genes for wet lab validation. Earlier efforts to build gene co-expression networks in P. falciparum have been limited to a single network inference method or gaining biological understanding for only a single gene and its interacting partners. Here, we explore multiple inference methods and aim to systematically predict functional annotations for all P. falciparum genes. We evaluate each inferred network based on how well it predicts existing gene-Gene Ontology (GO) term annotations using network clustering and leave-one-out crossvalidation. We assess overlaps of the different networks' edges (gene co-expression relationships), as well as predicted functional knowledge. The networks' edges are overall complementary: 47-85% of all edges are unique to each network. In terms of the accuracy of predicting gene functional annotations, all networks yielded relatively high precision (as high as 87% for the network inferred using mutual information), but the highest recall reached was below 15%. All networks having low recall means that none of them capture a large amount of all existing gene-GO term annotations. In fact, their annotation predictions are highly complementary, with the largest pairwise overlap of only 27%. We provide ranked lists of inferred gene-gene interactions and predicted gene-GO term annotations for future use and wet lab validation by the malaria community. CONCLUSIONS: The different networks seem to capture different aspects of the P. falciparum biology in terms of both inferred interactions and predicted gene functional annotations. Thus, relying on a single network inference method should be avoided when possible. SUPPLEMENTARY DATA: Attached.

Two Novel Variants in MITF and PAX3 Associated With Splashed White Phenotypes in Horses.

Mutations causing depigmentation are relatively common in Equus caballus (horse). Over 40 alleles in multiple genes are associated with increased white spotting (as of February 2023). The splashed white phenotype, a coat spotting pattern described as appearing like the horse has been splashed with white paint, was previously associated with variants in the PAX3 and MITF genes. Both genes encode transcription factors known to control melanocyte migration and pigmentation. We report two novel mutations, a stop-gain mutation in PAX3 (XM_005610643.3:c.927C>T, ECA6:11,196,181, EquCab3.0) and a missense mutation in a binding domain of MITF (NM_001163874.1:c.993A>T, ECA16:21,559,940, EquCab3.0), each with a strong association with increased depigmentation in Pura Raza Española horses (P = 1.144E-11, N = 30, P = 4.441E-16, N = 39 respectively). Using a quantitative method to score depigmentation, the PAX3 and MITF mutations were found to have average white scores of 25.50 and 24.45, respectively, compared to the average white coat spotting score of 1.89 in the control set. The functional impact for each mutation was predicted to be moderate to extreme (I-TASSER, SMART, Variant Effect Predictor, SIFT). We propose to designate the MITF mutant allele as Splashed White 9 and the PAX3 mutant allele as Splashed White 10 per convention.

5'UTR Variant in KIT Associated With White Spotting in Horses.

Mutations in KIT, a gene that influences melanoblast migration and pigmentation, often result in mammalian white spotting. As of February 2023, over 30 KIT variants associated with white spotting were documented in Equus caballus (horse). Here we report an association of increased white spotting on the skin and coat with a variant in the 5'UTR of KIT (rs1149701677: g.79,618,649A>C). Horses possessing at least one alternate allele demonstrate phenotypic characteristics similar to other KIT mutations: clear borders around unpigmented regions on the body, face, and limbs. Using a quantitative measure of depigmentation, we observed an average white score of 10.70 among individuals with rs1149701677, while the average score of the control, homozygous reference sample was 2.23 (P = 1.892e-11, n = 109, t-test). The rs1149701677 site has a cross-species conservation score of 3.4, one of the highest scores across the KIT 5'UTR, implying regulatory importance for this site. Ensembl also predicted a "moderately impactful" functional effect for the rs1149701677 variant. We propose that this single nucleotide variant likely alters the regulation of KIT, which in turn may disrupt melanoblast migration causing an increase in white spotting on the coat. Alternatively, the rs1149701677 variant may be in linkage with another nearby variant with an as-yet-undiscovered functional impact. We propose to term this new allele "Holiday White" or W35 based on conventional nomenclature.

Refractory bradycardia and hypotension in patients with autonomic dysfunction treated with pseudoephedrine.

We describe a man in his 40s with a history of chronic intranasal cocaine use and C5-C7 incomplete quadriplegia complicated by neurogenic orthostatic hypotension, admitted to the intensive care unit for worsening bradycardia and hypotension requiring initiation of dopamine and an increase of his home midodrine dose. The patient experienced refractory bradycardia and hypotension with weaning of dopamine, and therefore a recommendation was made to add pseudoephedrine to his current regimen. This case describes the addition of pseudoephedrine to facilitate weaning off intravenous vasopressors within 24 hours in a patient with refractory bradycardia and hypotension secondary to autonomic dysfunction.

An Insight Into Pathophysiology, Epidemiology, and Management of Cardiovascular Complications of SARS-CoV-2 Infection, Post-acute COVID Syndrome, and COVID Vaccine.

Coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a pandemic health emergency in March 2020. Elderly patients and those with pre-existing medical conditions including cardiovascular disease are at increased risk of developing severe disease. Not only is the viral infection with SARS-CoV-2 associated with higher mortality in patients with underlying cardiovascular disease, but development of cardiovascular complications is also common in patients with COVID-19. Even after recovery from the acute illness, post-acute COVID syndrome with cardiopulmonary manifestations can occur in some patients. Additionally, there are rare but increasingly recognized adverse events, including cardiovascular side effects, reported with currently available COVID-19 vaccines. In this review, we discuss the most common cardiovascular complications of SARS-CoV-2 and COVID-19 vaccines, cardiopulmonary manifestations of post-acute COVID syndrome and the current evidence-based guidance on the management of such complications.

A KIT Variant Associated with Increased White Spotting Epistatic to MC1R Genotype in Horses (Equus caballus).

Over 40 identified genetic variants contribute to white spotting in the horse. White markings and spotting are under selection for their impact on the economic value of an equine, yet many phenotypes have an unknown genetic basis. Previous studies also demonstrate an interaction between MC1R and ASIP pigmentation loci and white spotting associated with KIT and MITF. We investigated two stallions presenting with a white spotting phenotype of unknown cause. Exon sequencing of the KIT and MITF candidate genes identified a missense variant in KIT (rs1140732842, NC_009146.3:g.79566881T>C, p.T391A) predicted by SIFT and PROVEAN as not tolerated/deleterious. Three independent observers generated an Average Grade of White (AGW) phenotype score for 147 individuals based on photographs. The KIT variant demonstrates a significant QTL association to AGW (p = 3.3 × 10−12). Association with the MC1R Extension locus demonstrated that, although not in LD, MC1R e/e (chestnut) individuals had higher AGW scores than MC1R E/- individuals (p = 3.09 × 10−17). We also report complete linkage of the previously reported KIT W19 allele to this missense variant. We propose to term this variant W34, following the standardized nomenclature for white spotting variants within the equine KIT gene, and report its epistatic interaction with MC1R.

Cyclical regression covariates remove the major confounding effect of cyclical developmental gene expression with strain-specific drug response in the malaria parasite Plasmodium falciparum.

BACKGROUND: The cyclical nature of gene expression in the intraerythrocytic development cycle (IDC) of the malaria parasite, Plasmodium falciparum, confounds the accurate detection of specific transcriptional differences, e.g. as provoked by the development of drug resistance. In lab-based studies, P. falciparum cultures are synchronized to remove this confounding factor, but the rapid detection of emerging resistance to artemisinin therapies requires rapid analysis of transcriptomes extracted directly from clinical samples. Here we propose the use of cyclical regression covariates (CRC) to eliminate the major confounding effect of developmentally driven transcriptional changes in clinical samples. We show that elimination of this confounding factor reduces both Type I and Type II errors and demonstrate the effectiveness of this approach using a published dataset of 1043 transcriptomes extracted directly from patient blood samples with different patient clearance times after treatment with artemisinin. RESULTS: We apply this method to two publicly available datasets and demonstrate its ability to reduce the confounding of differences in transcript levels due to misaligned intraerythrocytic development time. Adjusting the clinical 1043 transcriptomes dataset with CRC results in detection of fewer functional categories than previously reported from the same data set adjusted using other methods. We also detect mostly the same functional categories, but observe fewer genes within these categories. Finally, the CRC method identifies genes in a functional category that was absent from the results when the dataset was adjusted using other methods. Analysis of differential gene expression in the clinical data samples that vary broadly for developmental stage resulted in the detection of far fewer transcripts in fewer functional categories while, at the same time, identifying genes in two functional categories not present in the unadjusted data analysis. These differences are consistent with the expectation that CRC reduces both false positives and false negatives with the largest effect on datasets from samples with greater variance in developmental stage. CONCLUSIONS: Cyclical regression covariates have immediate application to parasite transcriptome sequencing directly from clinical blood samples and to cost-constrained in vitro experiments.

Metabolomics Approaches to Dereplicate Natural Products from Coral-Derived Bioactive Bacteria.

Stony corals (Scleractinia) are invertebrates that form symbiotic relationships with eukaryotic algal endosymbionts and the prokaryotic microbiome. The microbiome has the potential to produce bioactive natural products providing defense and resilience to the coral host against pathogenic microorganisms, but this potential has not been extensively explored. Bacterial pathogens can pose a significant threat to corals, with some species implicated in primary and opportunistic infections of various corals. In response, probiotics have been proposed as a potential strategy to protect corals in the face of increased incidence of disease outbreaks. In this study, we screened bacterial isolates from healthy and diseased corals for antibacterial activity. The bioactive extracts were analyzed using untargeted metabolomics. Herein, an UpSet plot and hierarchical clustering analyses were performed to identify isolates with the largest number of unique metabolites. These isolates also displayed different antibacterial activities. Through application of in silico and experimental approaches coupled with genome analysis, we dereplicated natural products from these coral-derived bacteria from Florida's coral reef environments. The metabolomics approach highlighted in this study serves as a useful resource to select probiotic candidates and enables insights into natural product-mediated chemical ecology in holobiont symbiosis.

Demystifying the Genetic Origins of the Mangalarga Horse Through the Influential Stallion Turbante J.O.

Pedigrees and horse written ancestry contain numerous inconsistencies and divergence between farm histories, owner accounts and registration records. In particular, the origins of the Brazilian Mangalarga, or "Mangalarga Paulista'' horse breed is controversial, and the breed's popular history claims that one of its most famous individuals, Turbante J.O., may have been sired by an unknown Hanoverian stallion. Turbante J.O. sired over 1678 offspring and is present in about 71% of the male pedigrees. We genotyped Turbante J.O. and 29 registered Mangalarga individuals using a commercially available ancestry service and compared genomic to pedigree-based estimates. DNA was extracted for this sire from frozen semen samples. Other breed-average genomic ancestries for the Arabian, Thoroughbred, Saddlebred, and Hanoverian were utilized for comparison. Pedigree-based inbreeding coefficient (Fped) of Turbante J.O. and the 17 other Mangalargas were analyzed, and while Turbante J.O.'s Fped is estimated to be 18.5%, the genomic-based inbreeding coefficient is 33%. Pedigree-based co-ancestry coefficients estimate that about 3% of his ancestry should reflect Thoroughbred and Arabian heritage, however, the genomic analysis of Turbante J.O. identified 100% Iberian ancestry, and 99% in common with other Mangalarga individuals followed by other autochthonous Brazilian breeds, with no evidence of Hanoverian parentage. We demonstrate higher pedigree-estimated inbreeding coefficient errors than previously reported, perhaps a result of the pedigree depth, and the ability of genomic ancestral analysis to answer questions that pedigree analyses cannot. Due to the genomic relatedness, these results may provide more detailed guidelines in maintaining genetic diversity in this breed through selective outbreeding.