Reply to Hussey et al.: The requirement for accurate diet-tissue discrimination factors for interpreting stable isotopes in sharks

Carbon and nitrogen stable isotope analyses have improved our understanding of food webs and movement patterns of aquatic organisms. These techniques have recently been applied to diet studies of elasmobranch fishes, but isotope turnover rates and isotope diet–tissue discrimination are still poorly understood for this group. We performed a diet switch experiment on captive sandbar sharks (Carcharhinus plumbeus) as a model shark species to determine tissue turnover rates for liver, whole blood, and white muscle. In a second experiment, we subjected captive coastal skates (Leucoraja spp.) to serial salinity reductions to measure possible impacts of tissue urea content on nitrogen stable isotope values. We extracted urea from spiny dogfish (Squalus acanthias) white muscle to test for effects on nitrogen stable isotopes. Isotope turnover was slow for shark tissues and similar to previously published estimates for stingrays and teleost fishes with low growth rates. Muscle isotope data would likely fail to capture seasonal migrations or diet switches in sharks, while liver and whole blood would more closely reflect shorter term movement or shifts in diet. Nitrogen stable isotope values of skate blood and skate and dogfish white muscle were not affected by tissue urea content, suggesting that available diet–tissue discrimination estimates for teleost fishes with similar physiologies would provide accurate estimates for elasmobranchs.     

Determination of the relative and absolute stereochemistry of a potent and α1A-selective adrenoceptor antagonist

The binding affinities and selectivities of antagonists Figure 1 and Scheme 2 for the α_1A-adrenoceptor are dependent on the stereochemical orientation of the groups at the C-4 and C-5 positions of the oxazolidinone ring. The unambiguous assignment of the relative and absolute configurations of the diastereomers of SNAP 7915 (Figure 1 and Scheme 2) is reported.     

Gastrointestinal microflora,food components and colon cancer prevention

Evidence that the intestinal microbiota is intrinsically linked with overall health, including cancer risk, is emerging. Moreover, its composition is not fixed but can be influenced by several dietary components. Dietary modifiers, including the consumption of live bacteria (probiotics) and indigestible or limited digestible food constituents such as oligosaccharides (prebiotics) and polyphenols or both (synbiotics), are recognized modifiers of the numbers and types of microbes and have been reported to reduce colon cancer risk experimentally. Microorganisms also have the ability to generate bioactive compounds from food components. Examples include equol from isoflavones, enterodiol and enterolactone from lignans and urolithins from ellagic acid, which have also been demonstrated to retard experimentally induced cancers. The gastrointestinal microbiota can also influence both sides of the energy balance equation, namely, as a factor influencing energy utilization from the diet and as a factor that influences host genes that regulate energy expenditure and storage. Because of the link between obesity and cancer incidence and mortality, this complex complexion deserves greater attention. Overall, a dynamic interrelationship exists between the intestinal microbiota and colon cancer risk, which can be modified by dietary components and eating behaviors.     

CTLA4 Autoimmunity-Associated Genotype Contributes to Severe Pulmonary Tuberculosis in an African Population

The gene of Cytotoxic T Lymphocyte-associated Antigen 4 (CTLA4), a negative regulator of T lymphocytes, contains a single-nucleotide polymorphism (SNP) at position +6230A->G (ct60A->G), which has been found associated with several autoimmune diseases and appears to reduce T-cell inhibitory activity. In Ghana, West Africa, we compared the frequencies of CTLA4 +6230 A/G and 6 haplotype-tagging SNPs in 2010 smear-positive, HIV-negative patients with pulmonary tuberculosis (TB) and 2346 controls matched for age, gender and ethnicity. We found no difference in allele frequencies between cases and controls. However, +6230A and a distinct CTLA4 haplotype and a diplotype comprising the +6230A allele were significantly less frequent among cases with large opacities in chest radiographs compared to those with small ones (P_{corrected [cor]} = 0.002, P_cor = 0.00045, P = 0.0005, respectively). This finding suggests that an increased T-cell activity associated with the CTLA4 +6230G allele contributes to pathology rather than to protection in pulmonary TB.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs

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