Biology subjects

Mor, S.

Publications and source records attributed to Mor, S..

4 recordsLinked to original sources

bioRxiv2026

Cross-Resistance Limits the Ability of Antimicrobial Peptide Combinations to Delay Resistance Evolution

AimsAntimicrobial peptide (AMP) combinations have been proposed to delay resistance evolution, but it remains unclear what properties of a peptide pair determine whether a combination reduces resistance evolution relative to its component AMPs used alone. One suggested factor is mode of action, yet this has rarely been tested experimentally. In the current study we have asked whether mode of action or physicochemical similarity between peptides better predicts which combinations delay resistance. MethodsWe evolved Staphylococcus aureus with six AMPs with reported membrane-targeting and intracellular-targeting activity, individually and in all 15 pairwise combinations. We quantified resistance evolution, cross-resistance and fitness costs across the full AMP panel, and performed whole-genome sequencing on 126 evolved lineages. ResultsResistance varied across AMPs and correlated with peptide chain length, not mode of action. Cross-resistance was associated with physicochemical similarity, and similar peptides selected for overlapping mutations. Most combinations reduced resistance relative to single-AMP treatment, but those whose components shared cross-resistance were less effective, channeling evolution into convergent trajectories that resolve both selective pressures at once. Notably, mode of action did not predict combination outcome. ConclusionsCross-resistance, not mode of action, is a key factor in determining AMP combination efficacy. Physicochemical distance between peptides may serve as a practical predictor for cross-resistance, enabling selection of AMP combinations that are more likely to constrain resistance evolution.

microbiology↗

bioRxiv2020

A preliminary ecological profile of Kyasanur Forest disease virus hosts among the mammalian wildlife of the Western Ghats, India

Kyasanur Forest disease (KFD) is one of Indias severe arboviruses capable of causing prolonged debilitating disease. It has been expanding beyond its historical endemic locus at an alarming rate over the last two decades. The natural nidus of this zoonosis is located in the monsoon rainforest of the Western Ghats, India, which is one of the worlds most important biodiversity hotspots. Definitive reservoir hosts for KFD virus (KFDV) have yet to be delineated, and thus much of the infection ecology of this virus, and its consequent transmission dynamics, remains uncertain. Given its unique biogeographical context, identifying ecological parameters of KFDV relevant to the virus epidemiology has been complex and challenging. The challenge has been exacerbated by diminished research efforts in wildlife surveillance over the last two decades, coinciding with the expansion of the range of KFD across the region. The current investigation sought to define a preliminary ecological profile of KFDV hosts based on their life history and feeding traits to aid in re-establishing targeted wildlife surveillance and to discern those ecological traits of wildlife hosts that may improve our understanding of KFD epidemiology. The importance of fast-living among KFDV hosts was of special interest with respect to the latter aim. We compared mammalian traits between host and non-host species using general additive models and phylogenetic generalised linear models. This study found that both body mass and forest forage were strongly associated with mammalian host infection status, but that reproductive life history traits were not. These findings will help in structuring ecologically based wildlife surveillance and field investigations, while also helping to parameterise novel epidemiological models of zoonotic infection risk that incorporate species functional traits in a region where biogeography, landscape ecology, and community ecology manifest extraordinary complexity, particularly under growing anthropogenic pressure.

ecology↗

bioRxiv2018

The wildlife-livestock interface modulates anthrax suitability in India

Anthrax is a potentially life-threatening bacterial disease that can circulate in wild and domestic animals and subsequently spillover to human contacts with devastating consequences for human and animal health, as well as livestock economies and ecosystem conservation. India has a high annual occurrence of anthrax in some regions, but a country-wide delineation of risk has not yet been undertaken. The current study modeled the geographic suitability of anthrax across India and its associated environmental features using a biogeographical application of machine learning. Both biotic and abiotic features contributed to risk across multiple scales of influence and the wildlife-livestock interface, using elephants as a wildlife sentinel species, was the dominant feature in delineating anthrax suitability. In addition, water-soil balance, soil chemistry, and historical forest loss were also influential. These findings suggest that the wildlife-livestock interface plays an important role in the cycling of anthrax in India. Prevention efforts targeted toward this interface, particularly within anthropogenic ecotones, may yield successes in reducing ongoing transmission between animal hosts and subsequent zoonotic transmission to humans.

epidemiology↗

bioRxiv2017

Climatic influence on the anthrax niche in warming northern latitudes

Climate change is impacting ecosystem structure and function, with potentially drastic downstream effects on human and animal health. Emerging zoonotic diseases are expected to be particularly vulnerable to climate and biodiversity disturbance. Anthrax is an archetypal zoonosis that manifests its most significant burden on vulnerable pastoralist communities. The current study sought to investigate the influence of temperature increases on the landscape suitability of anthrax in the temperate, boreal, and arctic North, where observed climate impact has been rapid. This study also explored the influence of climate relative to more traditional factors, such as livestock distribution, ungulate biodiversity, and soil-water balance, in demarcating high risk landscapes. Machine learning was used to model landscape suitability as the ecological niche of anthrax in northern latitudes. The model identified climate, livestock density and wild ungulate species richness as the most influential landscape features in predicting suitability. These findings highlight the significance of warming temperatures for anthrax ecology in northern latitudes, and suggest potential mitigating effects of interventions targeting megafauna biodiversity conservation in grassland ecosystems, and animal health promotion among small to midsize livestock herds.\n\nSignificance StatementWe present evidence that a warming climate may be associated with the current distribution of anthrax risk in the temperate, boreal, and arctic North. Moreover, projected warming over the coming decades was associated with substantive expansion of this risk. In addition, livestock distribution, ungulate biodiversity, and soil-water balance were also influential to anthrax risk. While these results are sobering for the future health of livestock and pastoralist communities in the northern latitudes, the coincident modulating effect of ungulate biodiversity may suggest targeted ecosystem conservation as a possible buffer against a growing anthrax niche.

epidemiology↗