Doctor of Philosophy, Ben Gurion University Of The Negev (2018)
Master of Science, Ben Gurion University Of The Negev (2015)
Bachelor of Science, Hebrew University Of Jerusalem (2010)
- The role of landscape and history on the genetic structure of peripheral populations of the Near Eastern fire salamander, Salamandra infraimmaculata, in Northern Israel CONSERVATION GENETICS 2019; 20 (4): 875–89
- Was inter-population connectivity of Neanderthals and modern humans the driver of the Upper Paleolithic transition rather than its product? QUATERNARY SCIENCE REVIEWS 2019; 217: 316–29
- Ecological dynamics of the vaginal microbiome in relation to health and disease AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY 2019; 220 (4): 324–35
Ecological dynamics of the vaginal microbiome in relation to health and disease.
American journal of obstetrics and gynecology
The bacterial composition of the vaginal microbiome is thought to be related to health and disease states of women. This microbiome is particularly dynamic, with compositional changes related to pregnancy, menstruation, and disease states such as bacterial vaginosis. In order to understand these dynamics and their impact on health and disease, ecological theories have been introduced to study the complex interactions between the many taxa in the vaginal bacterial ecosystem. The goal of this review is to introduce the ecological principles that are used in the study of the vaginal microbiome and its dynamics, and to review the application of ecology to vaginal microbial communities with respect to health and disease. While applications of vaginal microbiome analysis and modulation have not yet been introduced into the routine clinical setting, a deeper understanding of its dynamics has the potential to facilitate development of future practices, for example in the context of postmenopausal vaginal symptoms, stratifying risk for obstetric complications, and control of sexually transmitted infections.
View details for PubMedID 30447213
Detecting hierarchical levels of connectivity in a population of Acacia tortilis at the northern edge of the species' global distribution: Combining classical population genetics and network analyses
2018; 13 (4): e0194901
Genetic diversity and structure of populations at the edge of the species' spatial distribution are important for potential adaptation to environmental changes and consequently, for the long-term survival of the species. Here, we combined classical population genetic methods with newly developed network analyses to gain complementary insights into the genetic structure and diversity of Acacia tortilis, a keystone desert tree, at the northern edge of its global distribution, where the population is under threat from climatic, ecological, and anthropogenic changes. We sampled A. tortilis from 14 sites along the Dead Sea region and the Arava Valley in Israel and in Jordan. In addition, we obtained samples from Egypt and Sudan, the hypothesized origin of the species. Samples from all sites were genotyped using six polymorphic microsatellite loci.Our results indicate a significant genetic structure in A. tortilis along the Arava Valley. This was detected at different hierarchical levels-from the basic unit of the subpopulation, corresponding to groups of trees within ephemeral rivers (wadis), to groups of subpopulations (communities) that are genetically more connected relative to others. The latter structure mostly corresponds to the partition of the major drainage basins in the area. Network analyses, combined with classical methods, allowed for the identification of key A. tortilis subpopulations in this region, characterized by their relatively high level of genetic diversity and centrality in maintaining gene flow in the population. Characterizing such key subpopulations may enable conservation managers to focus their efforts on certain subpopulations that might be particularly important for the population's long-term persistence, thus contributing to species conservation within its peripheral range.
View details for PubMedID 29649222