An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study.

BACKGROUND AIMS: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence (AI) in a global cohort, we sought to derive and validate an enhanced prognostic model. APPROACH AND RESULTS: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled AH patients per NIAAA criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day post-admission mortality, three AI algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined via Bayesian updating, integrating the derivation cohort's average 90-day mortality with each center's approximate mortality rate to produce post-test probabilities. The ALCoholic Hepatitis Artificial INtelligence (ALCHAIN) Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30-day) and 27.9% (90-day) in the derivation cohort, versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779 - 0.844) and 0.799 (0.769 - 0.830), significantly surpassing legacy models like Maddrey's Discriminant Function, MELD variations, ABIC, Glasgow, and modified Glasgow Scores (p<0.001). ALCHAIN Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCHAIN Ensemble score>0.20 in both derivation and validation cohorts. CONCLUSIONS: Harnessing AI within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it's accessible at: https://aihepatology.shinyapps.io/ALCHAIN/.

Experimental evolution of Pseudomonas aeruginosa to colistin in spatially confined microdroplets identifies evolutionary trajectories consistent with adaptation in microaerobic lung environments.

Antibiotic resistance is a continuing global health crisis. Identifying the evolutionary trajectories leading to increased antimicrobial resistance can be critical to the discovery of biomarkers for clinical diagnostics and new targets for drug discovery. While the combination of patient data and in vitro experimental evolution has been remarkably successful in extending our understanding of antimicrobial resistance, it can be difficult for in vitro methods to recapitulate the spatial structure and consequent microenvironments that characterize in vivo infection. Notably, in cystic fibrosis (CF) patients, changes to either the PmrA/PmrB or PhoP/PhoQ two-component systems have been identified as critical drivers for high levels of colistin and polymyxin resistance. When using microfluidic emulsions to provide spatially structured, low-competition environments, we found that adaptive mutations to phoQ were more successful than pmrB in increasing colistin resistance. Conversely, mutations to pmrB were readily identified using well-mixed unstructured cultures. We found that oxygen concentration gradients within the microdroplet emulsions favored adaptive changes to the PhoP/PhoQ pathway consistent with microaerobic conditions that can be found in the lungs of CF patients. We also observed mutations linked to hallmark adaptations to the CF lung environment, such as loss of motility and loss of O antigen biosynthesis (wbpL). Mutation to wbpL, in addition to causing loss of O antigen, was additionally shown to confer moderately increased colistin resistance. Taken together, our data suggest that distinct evolutionary trajectories to colistin resistance may be shaped by the microaerobic partitioning and spatial separation imposed within the CF lung.IMPORTANCEAntibiotic resistance remains one of the great challenges confronting public health in the world today. Individuals with compromised immune systems or underlying health conditions are often at an increased for bacterial infections. Patients with cystic fibrosis (CF) produce thick mucus that clogs airways and provides a very favorable environment for infection by bacteria that further decrease lung function and, ultimately, mortality. CF patients are often infected by bacteria such as Pseudomonas aeruginosa early in life and experience a series of chronic infections that, over time, become increasingly difficult to treat due to increased antibiotic resistance. Colistin is a major antibiotic used to treat CF patients. Clinical and laboratory studies have identified PmrA/PmrB and PhoP/PhoQ as responsible for increased resistance to colistin. Both have been identified in CF patient lungs, but why, in some cases, is it one and not the other? In this study, we show that distinct evolutionary trajectories to colistin resistance may be favored by the microaerobic partitioning found within the damaged CF lung.

MELD 3.0 adequately predicts mortality and renal replacement therapy requirements in patients with alcohol-associated hepatitis.

Background & Aims: Model for End-Stage Liver Disease (MELD) score better predicts mortality in alcohol-associated hepatitis (AH) but could underestimate severity in women and malnourished patients. Using a global cohort, we assessed the ability of the MELD 3.0 score to predict short-term mortality in AH. Methods: This was a retrospective cohort study of patients admitted to hospital with AH from 2009 to 2019. The main outcome was all-cause 30-day mortality. We compared the AUC using DeLong's method and also performed a time-dependent AUC with competing risks analysis. Results: A total of 2,124 patients were included from 28 centres from 10 countries on three continents (median age 47.2 ± 11.2 years, 29.9% women, 71.3% with underlying cirrhosis). The median MELD 3.0 score at admission was 25 (20-33), with an estimated survival of 73.7% at 30 days. The MELD 3.0 score had a better performance in predicting 30-day mortality (AUC:0.761, 95%CI:0.732-0.791) compared with MELD sodium (MELD-Na; AUC: 0.744, 95% CI: 0.713-0.775; p = 0.042) and Maddrey's discriminant function (mDF) (AUC: 0.724, 95% CI: 0.691-0.757; p = 0.013). However, MELD 3.0 did not perform better than traditional MELD (AUC: 0.753, 95% CI: 0.723-0.783; p = 0.300) and Age-Bilirubin-International Normalised Ratio-Creatinine (ABIC) (AUC:0.757, 95% CI: 0.727-0.788; p = 0.765). These results were consistent in competing-risk analysis, where MELD 3.0 (AUC: 0.757, 95% CI: 0.724-0.790) predicted better 30-day mortality compared with MELD-Na (AUC: 0.739, 95% CI: 0.708-0.770; p = 0.028) and mDF (AUC:0.717, 95% CI: 0.687-0.748; p = 0.042). The MELD 3.0 score was significantly better in predicting renal replacement therapy requirements during admission compared with the other scores (AUC: 0.844, 95% CI: 0.805-0.883). Conclusions: MELD 3.0 demonstrated better performance compared with MELD-Na and mDF in predicting 30-day and 90-day mortality, and was the best predictor of renal replacement therapy requirements during admission for AH. However, further prospective studies are needed to validate its extensive use in AH. Impact and implications: Severe AH has high short-term mortality. The establishment of treatments and liver transplantation depends on mortality prediction. We evaluated the performance of the new MELD 3.0 score to predict short-term mortality in AH in a large global cohort. MELD 3.0 performed better in predicting 30- and 90-day mortality compared with MELD-Na and mDF, but was similar to MELD and ABIC scores. MELD 3.0 was the best predictor of renal replacement therapy requirements. Thus, further prospective studies are needed to support the wide use of MELD 3.0 in AH.

Determining Prognosis of ALD and Alcohol-associated Hepatitis.

Alcohol-associated hepatitis has a poor prognosis in terms of short-term mortality and often presents with symptoms, such as jaundice, acute renal failure, and ascites. There are many prognostic models that have been developed to predict short-term and long-term mortality in these patients. Current prognostic models can be divided into static scores, which are measured at admission, and dynamic models, which measure baseline and after a certain amount of time. The efficacy of these models in predicting short-term mortality is disputed. Numerous studies across the world have compared prognostic models, such as the Maddrey's discriminant function, the model for end-stage liver disease score, model for end-stage liver disease score-Na, Glasgow alcohol-associated hepatitis score, and the age-bilirubin-international normalized ratio-creatinine (ABIC) score, to each other to determine which score is more useful for a particular context. There are also prognostic markers such as liver biopsy, breath biomarkers, and acute kidney injury that are able to predict mortality. The accuracy of these scores is a key to determining when treatment with corticosteroids is futile since there is an increased risk of infection in those treated with it. Furthermore, although these scores are helpful in predicting short-term mortality, the only factor that is able to predict long-term mortality in patients with alcohol-related liver disease is abstinence. Numerous studies have proven that even though corticosteroids provide a treatment for alcohol-associated hepatitis, it is a temporary one, at best. The purpose of this paper is to compare the historical models to current ones in their ability to predict mortality in patients with alcohol-related liver disease by analyzing multiple studies that have examined these prognostic markers. This paper also isolates the knowledge gaps in the ability to delineate which patients would benefit from corticosteroids and patients who would not and provides potential models for the future that could narrow this gap.

Enolpyruvate transferase MurAAA149E, identified during adaptation of Enterococcus faecium to daptomycin, increases stability of MurAA-MurG interaction.

Daptomycin (DAP) is an antibiotic frequently used as a drug of last resort against vancomycin-resistant enterococci. One of the major challenges when using DAP against vancomycin-resistant enterococci is the emergence of resistance, which is mediated by the cell-envelope stress system LiaFSR. Indeed, inhibition of LiaFSR signaling has been suggested as a strategy to "resensitize" enterococci to DAP. In the absence of LiaFSR, alternative pathways mediating DAP resistance have been identified, including adaptive mutations in the enolpyruvate transferase MurAA (MurAAA149E), which catalyzes the first committed step in peptidoglycan biosynthesis; however, how these mutations confer resistance is unclear. Here, we investigated the biochemical basis for MurAAA149E-mediated adaptation to DAP to determine whether such an alternative pathway would undermine the potential efficacy of therapies that target the LiaFSR pathway. We found cells expressing MurAAA149E had increased susceptibility to glycoside hydrolases, consistent with decreased cell wall integrity. Furthermore, structure-function studies of MurAA and MurAAA149E using X-ray crystallography and biochemical analyses indicated only a modest decrease in MurAAA149E activity, but a 16-fold increase in affinity for MurG, which performs the last intracellular step of peptidoglycan synthesis. Exposure to DAP leads to mislocalization of cell division proteins including MurG. In Bacillus subtilis, MurAA and MurG colocalize at division septa and, thus, we propose MurAAA149E may contribute to DAP nonsusceptibility by increasing the stability of MurAA-MurG interactions to reduce DAP-induced mislocalization of these essential protein complexes.

Intracellular Experimental Evolution of Francisella tularensis Subsp. holarctica Live Vaccine Strain (LVS) to Antimicrobial Resistance.

In vitro experimental evolution has complemented clinical studies as an excellent tool to identify genetic changes responsible for the de novo evolution of antimicrobial resistance. However, the in vivo context for adaptation contributes to the success of particular evolutionary trajectories, especially in intracellular niches where the adaptive landscape of virulence and resistance are strongly coupled. In this work, we designed an ex vivo evolution approach to identify evolutionary trajectories responsible for antibiotic resistance in the Live Vaccine Strain (LVS) of Francisella tularensis subsp. holarctica while being passaged to increasing ciprofloxacin (CIP) and doxycycline (DOX) concentrations within macrophages. Overall, adaptation within macrophages advanced much slower when compared to previous in vitro evolution studies reflecting a limiting capacity for the expansion of adaptive mutations within the macrophage. Longitudinal genomic analysis identified resistance conferring gyrase mutations outside the Quinolone Resistance Determining Region. Strikingly, FupA/B mutations that are uniquely associated with in vitro CIP resistance in Francisella were not observed ex vivo, reflecting the coupling of intracellular survival and resistance during intracellular adaptation. To our knowledge, this is the first experimental study demonstrating the ability to conduct experimental evolution to antimicrobial resistance within macrophages. The results provide evidence of differences in mutational profiles of populations adapted to the same antibiotic in different environments/cellular compartments and underscore the significance of host mediated stress during resistance evolution.

Mutational Switch-Backs Can Accelerate Evolution of Francisella to a Combination of Ciprofloxacin and Doxycycline.

Combination antimicrobial therapy has been considered a promising strategy to combat the evolution of antimicrobial resistance. Francisella tularensis is the causative agent of tularemia and in addition to being found in the nature, is recognized as a threat agent that requires vigilance. We investigated the evolutionary outcome of adapting the Live Vaccine Strain (LVS) of F. tularensis subsp. holarctica to two non-interacting drugs, ciprofloxacin and doxycycline, individually, sequentially, and in combination. Despite their individual efficacies and independence of mechanisms, evolution to the combination arose on a shorter time scale than evolution to the two drugs sequentially. We conducted a longitudinal mutational analysis of the populations evolving to the drug combination, genetically reconstructed the identified evolutionary pathway, and carried out biochemical validation. We discovered that, after the appearance of an initial weak generalist mutation (FupA/B), each successive mutation alternated between adaptation to one drug or the other. In combination, these mutations allowed the population to more efficiently ascend the fitness peak through a series of evolutionary switch-backs. Clonal interference, weak pleiotropy, and positive epistasis also contributed to combinatorial evolution. This finding suggests that the use of this non-interacting drug pair against F. tularensis may render both drugs ineffective because of mutational switch-backs that accelerate evolution of dual resistance.

Evolution of Enterococcus faecium in Response to a Combination of Daptomycin and Fosfomycin Reveals Distinct and Diverse Adaptive Strategies.

Infections caused by vancomycin-resistant Enterococcus faecium (VREfm) are an important public health threat. VREfm isolates have become increasingly resistant to the front-line antibiotic daptomycin (DAP). As such, the use of DAP combination therapies with other antibiotics like fosfomycin (FOS) has received increased attention. Antibiotic combinations could extend the efficacy of currently available antibiotics and potentially delay the onset of further resistance. We investigated the potential for E. faecium HOU503, a clinical VREfm isolate that is DAP and FOS susceptible, to develop resistance to a DAP-FOS combination. Of particular interest was whether the genetic drivers for DAP-FOS resistance might be epistatic and, thus, potentially decrease the efficacy of a combinatorial approach in either inhibiting VREfm or in delaying the onset of resistance. We show that resistance to DAP-FOS could be achieved by independent mutations to proteins responsible for cell wall synthesis for FOS and in altering membrane dynamics for DAP. However, we did not observe genetic drivers that exhibited substantial cross-drug epistasis that could undermine the DAP-FOS combination. Of interest was that FOS resistance in HOU503 was largely mediated by changes in phosphoenolpyruvate (PEP) flux as a result of mutations in pyruvate kinase (pyk). Increasing PEP flux could be a readily accessible mechanism for FOS resistance in many pathogens. Importantly, we show that HOU503 was able to develop DAP resistance through a variety of biochemical mechanisms and was able to employ different adaptive strategies. Finally, we showed that the addition of FOS can prolong the efficacy of DAP and slow down DAP resistance in vitro.

Identification of Evolutionary Trajectories Associated with Antimicrobial Resistance Using Microfluidics.

In vitro experimental evolution of pathogens to antibiotics is commonly used for the identification of clinical biomarkers associated with antibiotic resistance. Microdroplet emulsions allow exquisite control of spatial structure, species complexity, and selection microenvironments for such studies. We investigated the use of monodisperse microdroplets in experimental evolution. Using Escherichia coli adaptation to doxycycline, we examined how changes in environmental conditions such as droplet size, starting lambda value, selection strength, and incubation method affected evolutionary outcomes. We also examined the extent to which emulsions could reveal potentially new evolutionary trajectories and dynamics associated with antimicrobial resistance. Interestingly, we identified both expected and unexpected evolutionary trajectories including large-scale chromosomal rearrangements and amplification that were not observed in suspension culture methods. As microdroplet emulsions are well-suited for automation and provide exceptional control of conditions, they can provide a high-throughput approach for biomarker identification as well as preclinical evaluation of lead compounds.

Daptomycin Resistance in Enterococcus faecium Can Be Delayed by Disruption of the LiaFSR Stress Response Pathway.

LiaFSR signaling plays a major role in mediating daptomycin (DAP) resistance in enterococci, and the lack of a functional LiaFSR pathway leads to DAP hypersusceptibility. Using in vitro experimental evolution, we evaluated how Enterococcus faecium with a liaR response regulator gene deletion evolved DAP resistance. We found that knocking out LiaFSR signaling significantly delayed the onset of resistance, but resistance could emerge eventually through various alternate mechanisms that were influenced by the environment.

Environment Shapes the Accessible Daptomycin Resistance Mechanisms in Enterococcus faecium.

Daptomycin binds to bacterial cell membranes and disrupts essential cell envelope processes, leading to cell death. Bacteria respond to daptomycin by altering their cell envelopes to either decrease antibiotic binding to the membrane or by diverting binding away from septal targets. In Enterococcus faecalis, daptomycin resistance is typically coordinated by the three-component cell envelope stress response system, LiaFSR. Here, studying a clinical strain of multidrug-resistant Enterococcus faecium containing alleles associated with activation of the LiaFSR signaling pathway, we found that specific environments selected for different evolutionary trajectories, leading to high-level daptomycin resistance. Planktonic environments favored pathways that increased cell surface charge via yvcRS upregulation of dltABCD and mprF, causing a reduction in daptomycin binding. Alternatively, environments favoring complex structured communities, including biofilms, evolved both diversion and repulsion strategies via divIVA and oatA mutations, respectively. Both environments subsequently converged on cardiolipin synthase (cls) mutations, suggesting the importance of membrane modification across strategies. Our findings indicate that E. faecium can evolve diverse evolutionary trajectories to daptomycin resistance that are shaped by the environment to produce a combination of resistance strategies. The accessibility of multiple and different biochemical pathways simultaneously suggests that the outcome of daptomycin exposure results in a polymorphic population of resistant phenotypes, making E. faecium a recalcitrant nosocomial pathogen.

The Essential Role of Hypermutation in Rapid Adaptation to Antibiotic Stress.

A common outcome of antibiotic exposure in patients and in vitro is the evolution of a hypermutator phenotype that enables rapid adaptation by pathogens. While hypermutation is a robust mechanism for rapid adaptation, it requires trade-offs between the adaptive mutations and the more common "hitchhiker" mutations that accumulate from the increased mutation rate. Using quantitative experimental evolution, we examined the role of hypermutation in driving the adaptation of Pseudomonas aeruginosa to colistin. Metagenomic deep sequencing revealed 2,657 mutations at ≥5% frequency in 1,197 genes and 761 mutations in 29 endpoint isolates. By combining genomic information, phylogenetic analyses, and statistical tests, we showed that evolutionary trajectories leading to resistance could be reliably discerned. In addition to known alleles such as pmrB, hypermutation allowed identification of additional adaptive alleles with epistatic relationships. Although hypermutation provided a short-term fitness benefit, it was detrimental to overall fitness. Alarmingly, a small fraction of the colistin-adapted population remained colistin susceptible and escaped hypermutation. In a clinical population, such cells could play a role in reestablishing infection upon withdrawal of colistin. We present here a framework for evaluating the complex evolutionary trajectories of hypermutators that applies to both current and emerging pathogen populations.

Using experimental evolution to identify druggable targets that could inhibit the evolution of antimicrobial resistance.

With multi-drug and pan-drug-resistant bacteria becoming increasingly common in hospitals, antibiotic resistance has threatened to return us to a pre-antibiotic era that would completely undermine modern medicine. There is an urgent need to develop new antibiotics and strategies to combat resistance that are substantially different from earlier drug discovery efforts. One such strategy that would complement current and future antibiotics would be a class of co-drugs that target the evolution of resistance and thereby extend the efficacy of specific classes of antibiotics. A critical step in the development of such strategies lies in understanding the critical evolutionary trajectories responsible for resistance and which proteins or biochemical pathways within those trajectories would be good candidates for co-drug discovery. We identify the most important steps in the evolution of resistance for a specific pathogen and antibiotic combination by evolving highly polymorphic populations of pathogens to resistance in a novel bioreactor that favors biofilm development. As the populations evolve to increasing drug concentrations, we use deep sequencing to elucidate the network of genetic changes responsible for resistance and subsequent in vitro biochemistry and often structure determination to determine how the adaptive mutations produce resistance. Importantly, the identification of the molecular steps, their frequency within the populations and their chronology within the evolutionary trajectory toward resistance is critical to assessing their relative importance. In this work, we discuss findings from the evolution of the ESKAPE pathogen, Pseudomonas aeruginosa to the drug of last resort, colistin to illustrate the power of this approach.

Experimental Evolution of Diverse Strains as a Method for the Determination of Biochemical Mechanisms of Action for Novel Pyrrolizidinone Antibiotics.

The continuing rise of multidrug resistant pathogens has made it clear that in the absence of new antibiotics we are moving toward a "postantibiotic" world, in which even routine infections will become increasingly untreatable. There is a clear need for the development of new antibiotics with truly novel mechanisms of action to combat multidrug resistant pathogens. Experimental evolution to resistance can be a useful tactic for the characterization of the biochemical mechanism of action for antibiotics of interest. Herein, we demonstrate that the use of a diverse panel of strains with well-annotated reference genomes improves the success of using experimental evolution to characterize the mechanism of action of a novel pyrrolizidinone antibiotic analog. Importantly, we used experimental evolution under conditions that favor strongly polymorphic populations to adapt a panel of three substantially different Gram-positive species (lab strain Bacillus subtilis and clinical strains methicillin-resistant Staphylococcus aureus MRSA131 and Enterococcus faecalis S613) to produce a sufficiently diverse set of evolutionary outcomes. Comparative whole genome sequencing (WGS) between the susceptible starting strain and the resistant strains was then used to identify the genetic changes within each species in response to the pyrrolizidinone. Taken together, the adaptive response across a range of organisms allowed us to develop a readily testable hypothesis for the mechanism of action of the CJ-16 264 analog. In conjunction with mitochondrial inhibition studies, we were able to elucidate that this novel pyrrolizidinone antibiotic is an electron transport chain (ETC) inhibitor. By studying evolution to resistance in a panel of different species of bacteria, we have developed an enhanced method for the characterization of new lead compounds for the discovery of new mechanisms of action.

Genome-wide analysis of the response to nitric oxide in uropathogenic Escherichia coli CFT073.

Uropathogenic Escherchia coli (UPEC) is the causative agent of urinary tract infections. Nitric oxide (NO) is a toxic water-soluble gas that is encountered by UPEC in the urinary tract. Therefore, UPEC probably requires mechanisms to detoxify NO in the host environment. Thus far, flavohaemoglobin (Hmp), an NO denitrosylase, is the only demonstrated NO detoxification system in UPEC. Here we show that, in E. coli strain CFT073, the NADH-dependent NO reductase flavorubredoxin (FlRd) also plays a major role in NO scavenging. We generated a mutant that lacks all known and candidate NO detoxification pathways (Hmp, FlRd and the respiratory nitrite reductase, NrfA). When grown and assayed anaerobically, this mutant expresses an NO-inducible NO scavenging activity, pointing to the existence of a novel detoxification mechanism. Expression of this activity is inducible by both NO and nitrate, and the enzyme is membrane-associated. Genome-wide transcriptional profiling of UPEC grown under anaerobic conditions in the presence of nitrate (as a source of NO) highlighted various aspects of the response of the pathogen to nitrate and NO. Several virulence-associated genes are upregulated, suggesting that host-derived NO is a potential regulator of UPEC virulence. Chromatin immunoprecipitation and sequencing was used to evaluate the NsrR regulon in CFT073. We identified 49 NsrR binding sites in promoter regions in the CFT073 genome, 29 of which were not previously identified in E. coli K-12. NsrR may regulate some CFT073 genes that do not have homologues in E. coli K-12.