Mutant phenotypes for thousands of bacterial genes of unknown function.

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.

Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning.

BACKGROUND: Pulmonary hypertension (PH) is life-threatening, and often diagnosed late in its course. We aimed to evaluate if a deep learning approach using electrocardiogram (ECG) data alone can detect PH and clinically important subtypes. We asked: does an automated deep learning approach to ECG interpretation detect PH and its clinically important subtypes? METHODS AND RESULTS: Adults with right heart catheterization or an echocardiogram within 90 days of an ECG at the University of California, San Francisco (2012-2019) were retrospectively identified as PH or non-PH. A deep convolutional neural network was trained on patients' 12-lead ECG voltage data. Patients were divided into training, development, and test sets in a ratio of 7:1:2. Overall, 5016 PH and 19,454 patients without PH were used in the study. The mean age at the time of ECG was 62.29 ± 17.58 years and 49.88% were female. The mean interval between ECG and right heart catheterization or echocardiogram was 3.66 and 2.23 days for patients with PH and patients without PH, respectively. In the test dataset, the model achieved an area under the receiver operating characteristic curve, sensitivity, and specificity, respectively of 0.89, 0.79, and 0.84 to detect PH; 0.91, 0.83, and 0.84 to detect precapillary PH; 0.88, 0.81, and 0.81 to detect pulmonary arterial hypertension, and 0.80, 0.73, and 0.76 to detect group 3 PH. We additionally applied the trained model on ECGs from participants in the test dataset that were obtained from up to 2 years before diagnosis of PH; the area under the receiver operating characteristic curve was 0.79 or greater. CONCLUSIONS: A deep learning ECG algorithm can detect PH and PH subtypes around the time of diagnosis and can detect PH using ECGs that were done up to 2 years before right heart catheterization/echocardiogram diagnosis. This approach has the potential to decrease diagnostic delays in PH.

Novel computational methods on electronic health record yields new estimates of transfusion-associated circulatory overload in populations enriched with high-risk patients.

BACKGROUND: Transfusion-associated circulatory overload (TACO) is a severe adverse reaction (AR) contributing to the leading cause of mortality associated with transfusions. As strategies to mitigate TACO have been increasingly adopted, an update of prevalence rates and risk factors associated with TACO using the growing sources of electronic health record (EHR) data can help understand transfusion safety. STUDY DESIGN AND METHODS: This retrospective study aimed to provide a timely and reproducible assessment of prevalence rates and risk factors associated with TACO. Novel natural language processing methods, now made publicly available on GitHub, were developed to extract ARs from 3178 transfusion reaction reports. Other patient-level data were extracted computationally from UCSF EHR between 2012 and 2022. The odds ratio estimates of risk factors were calculated using a multivariate logistic regression analysis with case-to-control matched on sex and age at a ratio of 1:5. RESULTS: A total of 56,208 patients received transfusions (total 573,533 units) at UCSF during the study period and 102 patients developed TACO. The prevalence of TACO was estimated to be 0.2% per patient (102/total 56,208). Patients with a history of coagulopathy (OR, 1.36; 95% CI, 1.04-1.79) and transplant (OR, 1.99; 95% CI, 1.48-2.68) were associated with increased odds of TACO. DISCUSSION: While TACO is a serious AR, events remained rare, even in populations enriched with high-risk patients. Novel computational methods can be used to find and continually surveil for transfusion ARs. Results suggest that patients with history or presence of coagulopathy and organ transplant should be carefully monitored to mitigate potential risks of TACO.

Legal Admissibility of the Rorschach and R-PAS: A Review of Research, Practice, and Case Law.

The special issue editors selected us to form an "adversarial collaboration" because our publications and teaching encompass both supportive and critical attitudes toward the Rorschach and its recently developed system for use, the Rorschach Performance Assessment System (R-PAS). We reviewed the research literature and case law to determine if the Rorschach and specifically R-PAS meet legal standards for admissibility in court. We included evidence on norms, reliability, validity, utility, general acceptance, forensic evaluator use, and response style assessment, as well as United States and selected European case law addressing challenges to mental examination motions, admissibility, and weight. Compared to other psychological tests, the Rorschach is not challenged at unusually high rates. Although the recently introduced R-PAS is not widely referenced in case law, evidence suggests that information from it is likely to be ruled admissible when used by a competent evaluator and selected variables yield scores that are sufficiently reliable and valid to evaluate psychological processes that inform functional psycholegal capacities. We identify effective and ethical but also inappropriate uses (e.g., psychological profiling) of R-PAS in criminal, civil, juvenile, and family court. We recommend specific research to clarify important aspects of R-PAS and advance its utility in forensic mental health assessment.

The genomic basis of army ant chemosensory adaptations.

The evolution of mass raiding has allowed army ants to become dominant arthropod predators in the tropics. Although a century of research has led to many discoveries about behavioural, morphological and physiological adaptations in army ants, almost nothing is known about the molecular basis of army ant biology. Here we report the genome of the iconic New World army ant Eciton burchellii, and show that it is unusually compact, with a reduced gene complement relative to other ants. In contrast to this overall reduction, a particular gene subfamily (9-exon ORs) expressed predominantly in female antennae is expanded. This subfamily has previously been linked to the recognition of hydrocarbons, key olfactory cues used in insect communication and prey discrimination. Confocal microscopy of the brain showed a corresponding expansion in a putative hydrocarbon response centre within the antennal lobe, while scanning electron microscopy of the antenna revealed a particularly high density of hydrocarbon-sensitive sensory hairs. E. burchellii shares these features with its predatory and more cryptic relative, the clonal raider ant. By integrating genomic, transcriptomic and anatomical analyses in a comparative context, our work thus provides evidence that army ants and their relatives possess a suite of modifications in the chemosensory system that may be involved in behavioural coordination and prey selection during social predation. It also lays the groundwork for future studies of army ant biology at the molecular level.

Genome-wide fitness assessment during diurnal growth reveals an expanded role of the cyanobacterial circadian clock protein KaiA.

The recurrent pattern of light and darkness generated by Earth's axial rotation has profoundly influenced the evolution of organisms, selecting for both biological mechanisms that respond acutely to environmental changes and circadian clocks that program physiology in anticipation of daily variations. The necessity to integrate environmental responsiveness and circadian programming is exemplified in photosynthetic organisms such as cyanobacteria, which depend on light-driven photochemical processes. The cyanobacterium Synechococcus elongatus PCC 7942 is an excellent model system for dissecting these entwined mechanisms. Its core circadian oscillator, consisting of three proteins, KaiA, KaiB, and KaiC, transmits time-of-day signals to clock-output proteins, which reciprocally regulate global transcription. Research performed under constant light facilitates analysis of intrinsic cycles separately from direct environmental responses but does not provide insight into how these regulatory systems are integrated during light-dark cycles. Thus, we sought to identify genes that are specifically necessary in a day-night environment. We screened a dense bar-coded transposon library in both continuous light and daily cycling conditions and compared the fitness consequences of loss of each nonessential gene in the genome. Although the clock itself is not essential for viability in light-dark cycles, the most detrimental mutations revealed by the screen were those that disrupt KaiA. The screen broadened our understanding of light-dark survival in photosynthetic organisms, identified unforeseen clock-protein interaction dynamics, and reinforced the role of the clock as a negative regulator of a nighttime metabolic program that is essential for S. elongatus to survive in the dark.

High-throughput interaction screens illuminate the role of c-di-AMP in cyanobacterial nighttime survival.

The broadly conserved signaling nucleotide cyclic di-adenosine monophosphate (c-di-AMP) is essential for viability in most bacteria where it has been studied. However, characterization of the cellular functions and metabolism of c-di-AMP has largely been confined to the class Bacilli, limiting our functional understanding of the molecule among diverse phyla. We identified the cyclase responsible for c-di-AMP synthesis and characterized the molecule's role in survival of darkness in the model photosynthetic cyanobacterium Synechococcus elongatus PCC 7942. In addition to the use of traditional genetic, biochemical, and proteomic approaches, we developed a high-throughput genetic interaction screen (IRB-Seq) to determine pathways where the signaling nucleotide is active. We found that in S. elongatus c-di-AMP is produced by an enzyme of the diadenylate cyclase family, CdaA, which was previously unexplored experimentally. A cdaA-null mutant experiences increased oxidative stress and death during the nighttime portion of day-night cycles, in which potassium transport is implicated. These findings suggest that c-di-AMP is biologically active in cyanobacteria and has non-canonical roles in the phylum including oxidative stress management and day-night survival. The pipeline and analysis tools for IRB-Seq developed for this study constitute a quantitative high-throughput approach for studying genetic interactions.

Redox crisis underlies conditional light-dark lethality in cyanobacterial mutants that lack the circadian regulator, RpaA.

Cyanobacteria evolved a robust circadian clock, which has a profound influence on fitness and metabolism under daily light-dark (LD) cycles. In the model cyanobacterium Synechococcus elongatus PCC 7942, a functional clock is not required for diurnal growth, but mutants defective for the response regulator that mediates transcriptional rhythms in the wild-type, regulator of phycobilisome association A (RpaA), cannot be cultured under LD conditions. We found that rpaA-null mutants are inviable after several hours in the dark and compared the metabolomes of wild-type and rpaA-null strains to identify the source of lethality. Here, we show that the wild-type metabolome is very stable throughout the night, and this stability is lost in the absence of RpaA. Additionally, an rpaA mutant accumulates excessive reactive oxygen species (ROS) during the day and is unable to clear it during the night. The rpaA-null metabolome indicates that these cells are reductant-starved in the dark, likely because enzymes of the primary nighttime NADPH-producing pathway are direct targets of RpaA. Because NADPH is required for processes that detoxify ROS, conditional LD lethality likely results from inability of the mutant to activate reductant-requiring pathways that detoxify ROS when photosynthesis is not active. We identified second-site mutations and growth conditions that suppress LD lethality in the mutant background that support these conclusions. These results provide a mechanistic explanation as to why rpaA-null mutants die in the dark, further connect the clock to metabolism under diurnal growth, and indicate that RpaA likely has important unidentified functions during the day.

Long-term mortality and causes of death among patients with mild traumatic brain injury: a 5-year multicenter study.

Objective: Undergoing mild traumatic brain injury (mTBI) increases mortality risk, but it is unclear what drives this finding. This study explored associations with mortality in patients with mTBI.Methods: This was a retrospective study of patients with mTBI and controls admitted to six level 1 trauma centers in 1/1/2009-12/31/2013. Mortality data were from the CDC National Death Index. Patients with mTBI were identified by ICD-9 code, Glasgow Coma Scale 13-15, Injury Severity Score (ISS) <16, and loss of consciousness ≤1 hour. Controls had hospital length of stay ≤24 hours, ISS<16, and no head injury.Results: This study included 964 patients with mTBI and 5,567 controls. mTBI was associated with a 47% increased 5-year mortality risk (HR = 1.47, 95% CL 1.08-2.01). Patients with mTBI were more likely to die of a neurodegenerative disease (17% vs 11%, P = .119). Cardiovascular (HR = 1.80, 95% CL 1.17-2.77), neurological (HR = 3.33, 95% CL 2.07-5.38), and respiratory (HR = 1.70, 95% CL 1.01-2.86) comorbidities were associated with mortality in patients with mTBI.Conclusions: Patients with mTBI are at increased mortality risk in the 5 years post-injury. Mortality in patients with mTBI was most influenced by preexisting conditions.

The transcriptomic signature of low aggression in honey bees resembles a response to infection.

BACKGROUND: Behavior reflects an organism's health status. Many organisms display a generalized suite of behaviors that indicate infection or predict infection susceptibility. We apply this concept to honey bee aggression, a behavior that has been associated with positive health outcomes in previous studies. We sequenced the transcriptomes of the brain, fat body, and midgut of adult sibling worker bees who developed as pre-adults in relatively high versus low aggression colonies. Previous studies showed that this pre-adult experience impacts both aggressive behavior and resilience to pesticides. We performed enrichment analyses on differentially expressed genes to determine whether variation in aggression resembles the molecular response to infection. We further assessed whether the transcriptomic signature of aggression in the brain is similar to the neuromolecular response to acute predator threat, exposure to a high-aggression environment as an adult, or adult behavioral maturation. RESULTS: Across all three tissues assessed, genes that are differentially expressed as a function of aggression significantly overlap with genes whose expression is modulated by a variety of pathogens and parasitic feeding. In the fat body, and to some degree the midgut, our data specifically support the hypothesis that low aggression resembles a diseased or parasitized state. However, we find little evidence of active infection in individuals from the low aggression group. We also find little evidence that the brain molecular signature of aggression is enriched for genes modulated by social cues that induce aggression in adults. However, we do find evidence that genes associated with adult behavioral maturation are enriched in our brain samples. CONCLUSIONS: Results support the hypothesis that low aggression resembles a molecular state of infection. This pattern is most robust in the peripheral fat body, an immune responsive tissue in the honey bee. We find no evidence of acute infection in bees from the low aggression group, suggesting the physiological state characterizing low aggression may instead predispose bees to negative health outcomes when they are exposed to additional stressors. The similarity of molecular signatures associated with the seemingly disparate traits of aggression and disease suggests that these characteristics may, in fact, be intimately tied.