Alphaflexivirus genomes in stony coral tissue loss disease-affected, disease-exposed, and disease-unexposed coral colonies in the U.S. Virgin Islands

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Veglia, A., Beavers, K., Van Buren, E., Meiling, S., Muller, E., Smith, T., Holstein, D., Apprill, A., Brandt, M., Mydlarz, L., & Correa, A. Alphaflexivirus genomes in stony coral tissue loss disease-affected, disease-exposed, and disease-unexposed coral colonies in the U.S. Virgin Islands. Microbiology Resource Announcements, 11(2), (2022): e01199–e01121, https://doi.org/10.1128/mra.01199-21.Stony coral tissue loss disease (SCTLD) is decimating Caribbean corals. Here, through the metatranscriptomic assembly and annotation of two alphaflexivirus-like strains, we provide genomic evidence of filamentous viruses in SCTLD-affected, -exposed, and -unexposed coral colonies. These data will assist in clarifying the roles of viruses in SCTLD.This work was supported by the National Science Foundation (Biological Oceanography) award numbers 1928753 to M.E.B. and T.B.S., 1928609 to A.M.S.C., 1928817 to E.M.M., 19228771 to L.D.M., 1927277 to D.M.H., and 1928761 to A.A., as well as by VI EPSCoR (NSF numbers 0814417 and 1946412)

Obesity-Associated Alterations in Inflammation, Epigenetics, and Mammary Tumor Growth Persist in Formerly Obese Mice

Using a murine model of basal-like breast cancer, we tested the hypothesis that chronic obesity, an established breast cancer risk and progression factor in women, induces mammary gland epigenetic reprogramming and increases mammary tumor growth. Moreover, we assessed whether the obesity-induced epigenetic and protumor effects are reversed by weight normalization. Ovariectomized female C57BL/6 mice were fed a control diet or diet-induced obesity (DIO) regimen for 17 weeks, resulting in a normal weight or obese phenotype, respectively. Mice on the DIO regimen were then randomized to continue the DIO diet or were switched to the control diet, resulting in formerly obese (FOb) mice with weights comparable to control mice. At week 24, all mice were orthotopically injected with MMTV-Wnt-1 mouse mammary tumor cells. Mean tumor volume, serum IL-6 levels, expression of pro-inflammatory genes in the mammary fat pad, and mammary DNA methylation profiles were similar in DIO and FOb mice, and higher than in controls. Many of the genes found to have obesity-associated hypermethylation in mice were also found to be hypermethylated in the normal breast tissue of obese versus non-obese human subjects, and nearly all of these concordant genes remained hypermethylated after significant weight loss in the FOb mice. Our findings suggest that weight normalization may not be sufficient to reverse the effects of chronic obesity on epigenetic reprogramming and inflammatory signals in the microenvironment that are associated with breast cancer progression

Applications of Machine Learning Algorithms for Coral Disease Fate in Caribbean Corals

The Caribbean is known as a coral disease “hot spot” due to the high prevalence of acute and chronic diseases that have plagued corals in the area. Two diseases, Stony Coral Tissue Loss Disease (SCTLD) and White Plague (WP), are common and infect many coral species. These two diseases have been studied in a genotype- matching study that looked at transcriptomics of baseline, and post-exposure to disease in four species of corals. While transcriptomic studies have improved our knowledge of host response, a knowledge gap regarding the disease risk corals have prior to disease exposure still exists. Understanding disease risk before an outbreak is an important step in modeling disease dynamics of corals as it will help conservation efforts and disease response protocols. One way to identify disease risk is the application of machine learning to identify patterns of expression based on disease outcome. By applying novel but proven layers of machine learning programs from medical research and using healthy corals whose disease fate are known, we can identify which biological processes are relevant to disease susceptibility. We examined six different types of machine learning algorithms for detection of presence/absence of genes and expression patterns correlated o whether the coral got disease when exposed or not. We will report what types of data these algorithms provide and how it can be applied for disease motoring and modeling.Texas Advanced Computing Center (TACC

Formation and Fate of Carbonyls in Potable Water Reuse Systems

Low molecular weight, uncharged compounds have been the subject of considerable study at advanced treatment plants employed for potable water reuse. However, previously identified compounds only account for a small fraction of the total dissolved organic carbon remaining after reverse osmosis treatment. Uncharged carbonyl compounds (e.g., aldehydes and ketones) formed during oxidation have rarely been monitored in potable water reuse systems. To determine the relative importance of these compounds to final product water quality, samples were collected from six potable water reuse facilities and one conventional drinking water treatment plant. Saturated carbonyl compounds (e.g., formaldehyde, acetone) and α,β-unsaturated aldehydes (e.g., acrolein, crotonaldehyde) were quantified with a sensitive new analytical method. Relatively high concentrations of carbonyls (i.e., above 7 μM) were observed after ozonation of wastewater effluent. Biological filtration reduced concentrations of carbonyls by over 90%. Rejection of the carbonyls during reverse osmosis was correlated with molecular weight, with concentrations decreasing by 33% to 58%. Transformation of carbonyls resulted in decreases in concentration of 10% to 90% during advanced oxidation, with observed decreases consistent with rate constants for reactions of the compounds with hydroxyl radicals. Overall, carbonyl compounds accounted for 19% to 38% of the dissolved organic carbon in reverse osmosis-treated water

Stony coral tissue loss disease induces transcriptional signatures of in situ degradation of dysfunctional Symbiodiniaceae

Stony coral tissue loss disease (SCTLD), one of the most pervasive and virulent coral diseases on record, affects over 22 species of reef-building coral and is decimating reefs throughout the Caribbean. To understand how different coral species and their algal symbionts (family Symbiodiniaceae) respond to this disease, we examine the gene expression profiles of colonies of five species of coral from a SCTLD transmission experiment. The included species vary in their purported susceptibilities to SCTLD, and we use this to inform gene expression analyses of both the coral animal and their Symbiodiniaceae. We identify orthologous coral genes exhibiting lineage-specific differences in expression that correlate to disease susceptibility, as well as genes that are differentially expressed in all coral species in response to SCTLD infection. We find that SCTLD infection induces increased expression of rab7, an established marker of in situ degradation of dysfunctional Symbiodiniaceae, in all coral species accompanied by genus-level shifts in Symbiodiniaceae photosystem and metabolism gene expression. Overall, our results indicate that SCTLD infection induces symbiophagy across coral species and that the severity of disease is influenced by Symbiodiniaceae identity