Rita R. Colwell’s research while affiliated with Loyola University Maryland and other places

Climate change is having increasingly profound effects on human health, notably those associated with the occurrence, distribution, and transmission of infectious diseases. The number of disparate ecological parameters and pathogens affected by climate change are vast and expansive. Disentangling the complex relationship between these variables is critical for the development of effective countermeasures against its effects. The pathogen Vibrio vulnificus, a naturally occurring aquatic bacterium that causes fulminant septicemia, represents a quintessential climate-sensitive organism. In this review, we use V. vulnificus as a model organism to elucidate the intricate network of interactions between climatic factors and pathogens, with the objective of identifying common patterns by which climate change is affecting their disease burden. Recent findings indicate that in regions native to V. vulnificus or related pathogens, climate-driven natural disasters are the chief contributors to their disease outbreaks. Concurrently, climate change is increasing the environmental suitability of areas non-endemic to their diseases, promoting a surge in their natural populations and transmission dynamics, thus elevating the risk of new outbreaks. We highlight potential risk factors and climatic drivers aggravating the threat of V. vulnificus transmission under both scenarios and propose potential measures for mitigating its impact. By defining the mechanisms by which climate change influences V. vulnificus disease burden, we aim to shed light on the transmission dynamics of related disease-causing agents, thereby laying the groundwork for early warning systems and broadly applicable control measures.

The adult skin microbiome contributes to skin homeostasis and generally comprises relatively low microbial complexity, especially sebaceous sites, where lipophilic Cutibacterium and Malassezia spp. predominate. Current understanding of the healthy skin microbiome derives predominantly from studies of western, industrialized populations, with limited representation of diverse cultures and lifestyles. In this study, the skin microbiome of a remote indigenous Yanomami community was investigated, revealing a complex microbial community comprised of 115 novel bacterial genomes. The bacterial community composition included genera common to western skin microbiota and additional diverse taxa, which formed multiplex interactions with a dominant eukaryote, Malassezia globosa. Metatranscriptome-derived functional attributes of the microbial communities contributed to skin homeostasis, fortifying barrier integrity via lipid metabolism and acid production and protecting against oxidative stress. The Yanomami skin microbiome comprised a suite of microbial taxa co-detected within their various surroundings. Longitudinal monitoring of Western expeditioner microbiome revealed acquisition of the Yanomami skin microbiome following immersion into the Amazon and subsequent loss upon return to an industrialized setting. These findings challenge the prevailing Western-centric view of what comprises a healthy adult skin microbiome, suggesting a diverse community that includes bacteria of environmental origin confers benefits not recognized in the current model of healthy skin. Importantly, we highlight the malleability of adult skin microbiome composition, which includes changes sustained by lifestyle modification.

Harmful algal blooms caused by cyanobacteria threaten aquatic ecosystems, the economy, and human health. Previous work has tried to identify the mechanisms that allow blooms to form, focusing on the role of nutrients. However, little is known about how introduced nutrients influence gene expression in situ. To address this knowledge gap, we used in situ mesocosms initiated with water experiencing a Microcystis bloom. We added pulses of nutrients that are commonly associated with anthropogenic sources to the mesocosms for 72 hours and collected samples for metatranscriptomics to examine how the physiological function of Microcystis and bloom status changed. The addition of nitrogen (N) as urea, but not the addition of PO4, resulted in conspicuous bloom persistence for at least 9 days after the final introduction of nutrients. The addition of urea initially resulted in the upregulation of photosynthesis machinery, as well as phosphate, carbon, and N transport and metabolism. Once Microcystis presumably became N-replete, upregulation of amino acid metabolism, microcystin biosynthesis, and other processes associated with biomass generation occurred. These capacities coincided with the upregulation of toxin-antitoxin systems, CRISPR-cas genes, and transposases suggesting that phage defense and genome rearrangement are critical in bloom persistence. Overall, our results show the stepwise transcriptional response of a Microcystis bloom to the introduction of nutrients, specifically urea, as it is sustained in a natural setting. The transcriptomic shifts observed herein may serve as markers of the longevity of blooms while providing insight into why Microcystis blooms over other cyanobacteria. IMPORTANCE Harmful algal blooms represent a threat to human health and ecosystems. Understanding why blooms persist may help us develop warning indicators of bloom persistence and create novel mitigation strategies. Using mesocosm experiments initiated with water with an active bloom, we measured the stepwise transcription changes of the toxin-producing cyanobacterium Microcystis in response to the addition of nutrients that are important in causing blooms. We found that nitrogen (N), but not phosphorus, promoted bloom longevity. The initial introduction of N resulted in the upregulation of genes involved in photosynthesis and N import. At later times in the bloom, upregulation of genes involved in biomass generation, phage protection, genomic rearrangement, and toxin production was observed. Our results suggest that Microcystis first fulfills nutritional requirements before investing energy in pathways associated with growth and protection against competitors, which allowed bloom persistence more than a week after the final addition of nutrients.

The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenic Vibrio spp. The waterborne pathogen, Vibrio vulnificus can invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination of V. vulnificus need to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll‐a (chl‐a) in locations with reported V. vulnificus infections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2‐month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl‐a values, was statistically linked to higher odds of V. vulnificus infection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.

The occurrence of cyanobacterial harmful algal blooms (cyanoHABs) is related to their physical and chemical environment. However, less is known about their associated microbial interactions and processes. In this study, cyanoHABs were analyzed as a microbial ecosystem, using 1 year of 16S rRNA sequencing and 70 metagenomes collected during the bloom season from Lake Okeechobee (Florida, USA). Biogeographical patterns observed in microbial community composition and function reflected ecological zones distinct in their physical and chemical parameters that resulted in bloom “hotspots” near major lake inflows. Changes in relative abundances of taxa within multiple phyla followed increasing bloom severity. Functional pathways that correlated with increasing bloom severity encoded organic nitrogen and phosphorus utilization, storage of nutrients, exchange of genetic material, phage defense, and protection against oxidative stress, suggesting that microbial interactions may promote cyanoHAB resilience. Cyanobacterial communities were highly diverse, with picocyanobacteria ubiquitous and oftentimes most abundant, especially in the absence of blooms. The identification of novel bloom-forming cyanobacteria and genomic comparisons indicated a functionally diverse cyanobacterial community with differences in its capability to store nitrogen using cyanophycin and to defend against phage using CRISPR and restriction-modification systems. Considering blooms in the context of a microbial ecosystem and their interactions in nature, physiologies and interactions supporting the proliferation and stability of cyanoHABs are proposed, including a role for phage infection of picocyanobacteria. This study displayed the power of “-omics” to reveal important biological processes that could support the effective management and prediction of cyanoHABs. IMPORTANCE Cyanobacterial harmful algal blooms pose a significant threat to aquatic ecosystems and human health. Although physical and chemical conditions in aquatic systems that facilitate bloom development are well studied, there are fundamental gaps in the biological understanding of the microbial ecosystem that makes a cyanobacterial bloom. High-throughput sequencing was used to determine the drivers of cyanobacteria blooms in nature. Multiple functions and interactions important to consider in cyanobacterial bloom ecology were identified. The microbial biodiversity of blooms revealed microbial functions, genomic characteristics, and interactions between cyanobacterial populations that could be involved in bloom stability and more coherently define cyanobacteria blooms. Our results highlight the importance of considering cyanobacterial blooms as a microbial ecosystem to predict, prevent, and mitigate them.

Antibiotics are often used to treat severe Vibrio infections, with third-generation cephalosporins and tetracyclines combined or fluoroquinolones alone being recommended by the US Centers for Disease Control and Prevention. Increases in antibiotic resistance of both environmental and clinical vibrios are of concern; however, limited longitudinal data have been generated among environmental isolates to inform how resistance patterns may be changing over time. Hence, we evaluated long-term trends in antibiotic resistance of vibrios isolated from Chesapeake Bay waters (Maryland) across two 3-year sampling periods (2009–2012 and 2019–2022). Vibrio parahaemolyticus (n = 134) and Vibrio vulnificus (n = 94) toxR-confirmed isolates were randomly selected from both sampling periods and tested for antimicrobial susceptibility against eight antibiotics using the Kirby-Bauer disk diffusion method. A high percentage (94%–96%) of V. parahaemolyticus isolates from both sampling periods were resistant to ampicillin and only 2%–6% of these isolates expressed intermediate resistance or resistance to third-generation cephalosporins, amikacin, tetracycline, and trimethoprim-sulfamethoxazole. Even lower percentages of resistant V. vulnificus isolates were observed and those were mostly recovered from 2009 to 2012, however, the presence of multiple virulence factors was observed. The frequency of multi-drug resistance was relatively low (6%–8%) but included resistance against antibiotics used to treat severe vibriosis in adults and children. All isolates were susceptible to ciprofloxacin, a fluoroquinolone, indicating its sustained efficacy as a first-line agent in the treatment of severe vibriosis. Overall, our data indicate that antibiotic resistance patterns among V. parahaemolyticus and V. vulnificus recovered from the lower Chesapeake Bay have remained relatively stable since 2009. IMPORTANCE Vibrio spp. have historically been susceptible to most clinically relevant antibiotics; however, resistance and intermediate-resistance have been increasingly recorded in both environmental and clinical isolates. Our data showed that while the percentage of multi-drug resistance and resistance to antibiotics was relatively low and stable across time, some Vibrio isolates displayed resistance and intermediate resistance to antibiotics typically used to treat severe vibriosis (e.g., third-generation cephalosporins, tetracyclines, sulfamethoxazole-trimethoprim, and aminoglycosides). Also, given the high case fatality rates observed with Vibrio vulnificus infections, the presence of multiple virulence factors in the tested isolates is concerning. Nevertheless, the continued susceptibility of all tested isolates against ciprofloxacin, a fluoroquinolone, is indicative of its use as an effective first-line treatment of severe Vibrio spp. infections stemming from exposure to Chesapeake Bay waters or contaminated seafood ingestion.

Large-scale population displacements arising from conflict-induced forced migration generate uncertainty and introduce several policy challenges. Addressing these concerns requires an interdisciplinary approach that integrates knowledge from both computational modeling and social sciences. We propose a generalized computational agent-based modeling framework grounded by Theory of Planned Behavior to model conflict-induced migration outflows within Ukraine during the start of that conflict in 2022. Existing migration modeling frameworks that attempt to address policy implications primarily focus on destination while leaving absent a generalized computational framework grounded by social theory focused on the conflict-induced region. We propose an agent-based framework utilizing a spatiotemporal gravity model and a Bi-threshold model over a Graph Dynamical System to update migration status of agents in conflict-induced regions at fine temporal and spatial granularity. This approach significantly outperforms previous work when examining the case of Russian invasion in Ukraine. Policy implications of the proposed framework are demonstrated by modeling the migration behavior of Ukrainian civilians attempting to flee from regions encircled by Russian forces. We also showcase the generalizability of the model by simulating a past conflict in Burundi, an alternative conflict setting. Results demonstrate the utility of the framework for assessing conflict-induced migration in varied settings as well as identifying vulnerable civilian populations.

The ongoing Russian aggression against Ukraine has forced over eight million people to migrate out of Ukraine. Understanding the dynamics of forced migration is essential for policy-making and for delivering humanitarian assistance. Existing work is hindered by a reliance on observational data which is only available well after the fact. In this work, we study the efficacy of a data-driven agent-based framework motivated by social and behavioral theory in predicting outflow of migrants as a result of conflict events during the initial phase of the Ukraine war. We discuss policy use cases for the proposed framework by demonstrating how it can leverage refugee demographic details to answer pressing policy questions. We also show how to incorporate conflict forecast scenarios to predict future conflict-induced migration flows. Detailed future migration estimates across various conflict scenarios can both help to reduce policymaker uncertainty and improve allocation and staging of limited humanitarian resources in crisis settings.

In 2023 human populations experienced multiple record‐breaking climate events, with widespread impacts on human health and well‐being. These events include extreme heat domes, drought, severe storms, flooding, and wildfires. Due to inherent lags in the climate system, we can expect such extremes to continue for multiple decades after reaching net zero carbon emissions. Unfortunately, despite these significant current and future impacts, funding for research in climate and health has lagged behind that for other geoscience and biomedical research. While some initial efforts from funding agencies are evident, there is still a significant need to increase the resources available for multidisciplinary research in the face of this issue. As a group of experts at this important intersection, we call for a more concerted effort to encourage interdisciplinary and policy‐relevant investigations into the detrimental health effects of continued climate change.