Co-evolution of interacting proteins through non-contacting and non-specific mutations.

Proteins often accumulate neutral mutations that do not affect current functions but can profoundly influence future mutational possibilities and functions. Understanding such hidden potential has major implications for protein design and evolutionary forecasting but has been limited by a lack of systematic efforts to identify potentiating mutations. Here, through the comprehensive analysis of a bacterial toxin-antitoxin system, we identified all possible single substitutions in the toxin that enable it to tolerate otherwise interface-disrupting mutations in its antitoxin. Strikingly, the majority of enabling mutations in the toxin do not contact and promote tolerance non-specifically to many different antitoxin mutations, despite covariation in homologues occurring primarily between specific pairs of contacting residues across the interface. In addition, the enabling mutations we identified expand future mutational paths that both maintain old toxin-antitoxin interactions and form new ones. These non-specific mutations are missed by widely used covariation and machine learning methods. Identifying such enabling mutations will be critical for ensuring continued binding of therapeutically relevant proteins, such as antibodies, aimed at evolving targets.

Feeding intolerance in critically ill patients with COVID-19.

BACKGROUND & AIMS: Early reports suggest significant difficulty with enteral feeding in critically ill COVID-19 patients. This study aimed to characterize the prevalence, clinical manifestations, and outcomes of feeding intolerance in critically ill patients with COVID-19. METHODS: We examined 323 adult patients with COVID-19 admitted to the intensive care units (ICUs) of Massachusetts General Hospital between March 11 and June 28, 2020 who received enteral nutrition. Systematic chart review determined prevalence, clinical characteristics, and hospital outcomes (ICU complications, length of stay, and mortality) of feeding intolerance. RESULTS: Feeding intolerance developed in 56% of the patients and most commonly manifested as large gastric residual volumes (83.9%), abdominal distension (67.2%), and vomiting (63.9%). Length of intubation (OR 1.05, 95% CI 1.03-1.08), ≥1 GI symptom on presentation (OR 0.76, 95% CI 0.59-0.97), and severe obesity (OR 0.29, 95% CI 0.13-0.66) were independently associated with development of feeding intolerance. Compared to feed-tolerant patients, patients with incident feeding intolerance were significantly more likely to suffer cardiac, renal, hepatic, and hematologic complications during their hospitalization. Feeding intolerance was similarly associated with poor outcomes including longer ICU stay (median [IQR] 21.5 [14-30] vs. 15 [9-22] days, P < 0.001), overall hospitalization time (median [IQR] 30.5 [19-42] vs. 24 [15-35], P < 0.001) and in-hospital mortality (33.9% vs. 16.1%, P < 0.001). Feeding intolerance was independently associated with an increased risk of death (HR 3.32; 95% CI 1.97-5.6). CONCLUSIONS: Feeding intolerance is a frequently encountered complication in critically ill COVID-19 patients in a large tertiary care experience and is associated with poor outcomes.

Finding the sources of missing heritability in a yeast cross.

For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic-mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this 'missing heritability' have been proposed. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits, and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50 per cent. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits.