Socio-ecology of the marsh rice rat (Oryzomys palustris) and the spatio-temporal distribution of Bayou virus in coastal Texas

Abstract

Abstract. Along the southeastern coast of the United States of America (USA), the marsh rice rat (Oryzomys palustris) is the primary host for the hantavirus genotype Bayou. According to the socio-ecological model for a territorial, polygamous species, females should be distributed across space and time by habitat resources and predation risks, whereas males should space themselves according to the degree of female aggregation and reproductive synchrony. To investigate how females affect the male-male transmission paradigm of Bayou virus, rodents were captured, marked, released, and re-captured in two macrohabitat types across a 30-month period. Microhabitat cover variables were quantified around the individual trap stations. A geodatabase was created from habitat and rodent capture data and analysed in a geographical information system. The ratio of breeding to non-breeding females was ~1:1, with breeding females overly dispersed and non-breeding females randomly dispersed. Spatial analyses revealed both macro-and microhabitat preferences in females. Compared to sero-negatives, higher proportions of seropositive adult males were found consistently within closer proximities to breeding females but not to non-breeding females, indicating that male locations were not driven simply by habitat selection. Activities to acquire dispersed receptive females could be an important driver of Bayou virus transmission among male hosts. To date, socio-ecological theory has received little attention as an investigative framework for studying pathogen dynamics in small, solitary mammals. Herein, we describe an interdisciplinary effort providing a novel approach to elucidate the complexity of hantavirus trafficking and maintenance in rodent populations of a coastal marsh ecosystem.

Attenuated Amiloride-Sensitive Current and Augmented Calcium-Activated Chloride Current in Marsh Rice Rat (Oryzomys palustris) Airways

“…Paralleling this finding, mRNA expression for CFTR was also decreased in rice rat cultures compared with mouse cultures. This diminished CFTR activity appears to have minimal negative effects in the rice rat airway, as they show no overt signs of lung disease, even as carriers of hantavirus (Holsomback et al., 2013). In CFTR knockout mice, and in humans and rats with CFTR mutations, TMEM16A is thought to compensate for loss of CFTR (Billet and Hanrahan, 2013, Clarke and Boucher, 1992, Tuggle et al., 2014).…”

Ecology of Neglected Rodent-Borne American Orthohantaviruses

“…Compounding more exposure opportunities for older individuals, higher prevalence in older males is assumed to result from increased aggression and competition, primarily for access to mates [70,71]. Associations of BAYV-infected male O. palustris with receptive females and non-infected males with non-receptive females [51] further supports the concept of reproductive behaviors as a primary driver of orthohantavirus transmission among wild rodents. Thus, some females likely become infected via allogrooming during copulative behaviors common in rodents (e.g., [72,73]).…”

“…In the absence of data on orthohantavirus presence in a particular area, host distributions may be useful as proxies, as rodent ranges and habitat types are often well-documented [25,47,48]. Several orthohantaviruses have been found throughout large extents of their host range, including BCCV [17,49], BAYV [50,51], and others, indicating that orthohantaviruses have the potential to be present throughout the entire range of host species. However, the use of virus genotypes causes confusion when determining the range of orthohantaviruses.…”

Viral competence data improves rodent reservoir predictions for American orthohantaviruses

“…Determining the reservoir host of a particular orthohantavirus can be challenging, as orthohantaviruses are difficult to isolate (Strandin et al 2020) and, like many infectious diseases, infection prevalence varies drastically across space and time (Walsh et al 2007;Vadell et al 2011;Holsomback et al 2013). However, predictive modeling enables the detection of novel hosts in the absence of field data and in turn facilitates targeted field surveillance that can ultimately be used to mitigate hazards posed by zoonotic viruses (Becker et al 2019).…”