Katharine Walter

All Publications

• Genomic insights into the ancient spread of Lyme disease across North America Nature Ecology & Evolution Walter, K. S., Carpi, G., Caccone, A., Diuk-Wasser, M. A. 2017; 1 (10): 1569–1576

  View details for DOI 10.1038/s41559-017-0282-8

• Identifying climate drivers of infectious disease dynamics: recent advances and challenges ahead. Proceedings. Biological sciences Metcalf, C. J., Walter, K. S., Wesolowski, A., Buckee, C. O., Shevliakova, E., Tatem, A. J., Boos, W. R., Weinberger, D. M., Pitzer, V. E. 2017; 284 (1860)

  Abstract

  Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

  View details for DOI 10.1098/rspb.2017.0901

  View details for PubMedID 28814655

  View details for PubMedCentralID PMC5563806

• Babesia microti from humans and ticks hold a genomic signature of strong population structure in the United States BMC GENOMICS Carpi, G., Walter, K. S., Ben Mamoun, C., Krause, P. J., Kitchen, A., Lepore, T. J., Dwivedi, A., Cornillot, E., Caccone, A., Diuk-Wasser, M. A. 2016; 17

  Abstract

  Babesia microti is an emerging tick-borne apicomplexan parasite with increasing geographic range and incidence in the United States. The rapid expansion of B. microti into its current distribution in the northeastern USA has been due to the range expansion of the tick vector, Ixodes scapularis, upon which the causative agent is dependent for transmission to humans.To reconstruct the history of B. microti in the continental USA and clarify the evolutionary origin of human strains, we used multiplexed hybrid capture of 25 B. microti isolates obtained from I. scapularis and human blood. Despite low genomic variation compared with other Apicomplexa, B. microti was strongly structured into three highly differentiated genetic clusters in the northeastern USA. Bayesian analyses of the apicoplast genomes suggest that the origin of the current diversity of B. microti in northeastern USA dates back 46 thousand years with a signature of recent population expansion in the last 1000 years. Human-derived samples belonged to two rarely intermixing clusters, raising the possibility of highly divergent infectious phenotypes in humans.Our results validate the multiplexed hybrid capture strategy for characterizing genome-wide diversity and relatedness of B. microti from ticks and humans. We find strong population structure in B. microti samples from the Northeast indicating potential barriers to gene flow.

  View details for DOI 10.1186/s12864-016-3225-x

  View details for Web of Science ID 000387183000009

  View details for PubMedID 27821055

• Vectors as Epidemiological Sentinels: Patterns of Within-Tick Borrelia burgdorferi Diversity PLOS PATHOGENS Walter, K. S., Carpi, G., Evans, B. R., Caccone, A., Diuk-Wasser, M. A. 2016; 12 (7)

  Abstract

  Hosts including humans, other vertebrates, and arthropods, are frequently infected with heterogeneous populations of pathogens. Within-host pathogen diversity has major implications for human health, epidemiology, and pathogen evolution. However, pathogen diversity within-hosts is difficult to characterize and little is known about the levels and sources of within-host diversity maintained in natural populations of disease vectors. Here, we examine genomic variation of the Lyme disease bacteria, Borrelia burgdorferi (Bb), in 98 individual field-collected tick vectors as a model for study of within-host processes. Deep population sequencing reveals extensive and previously undocumented levels of Bb variation: the majority (~70%) of ticks harbor mixed strain infections, which we define as levels Bb diversity pre-existing in a diverse inoculum. Within-tick diversity is thus a sample of the variation present within vertebrate hosts. Within individual ticks, we detect signatures of positive selection. Genes most commonly under positive selection across ticks include those involved in dissemination in vertebrate hosts and evasion of the vertebrate immune complement. By focusing on tick-borne Bb, we show that vectors can serve as epidemiological and evolutionary sentinels: within-vector pathogen diversity can be a useful and unbiased way to survey circulating pathogen diversity and identify evolutionary processes occurring in natural transmission cycles.

  View details for DOI 10.1371/journal.ppat.1005759

  View details for Web of Science ID 000383366400039

  View details for PubMedID 27414806

• Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES Walter, K. S., Pepin, K. M., Webb, C. T., Gaff, H. D., Krause, P. J., Pitzer, V. E., Diuk-Wasser, M. A. 2016; 283 (1832)

  Abstract

  Modelling the spatial spread of vector-borne zoonotic pathogens maintained in enzootic transmission cycles remains a major challenge. The best available spatio-temporal data on pathogen spread often take the form of human disease surveillance data. By applying a classic ecological approach-occupancy modelling-to an epidemiological question of disease spread, we used surveillance data to examine the latent ecological invasion of tick-borne pathogens. Over the last half-century, previously undescribed tick-borne pathogens including the agents of Lyme disease and human babesiosis have rapidly spread across the northeast United States. Despite their epidemiological importance, the mechanisms of tick-borne pathogen invasion and drivers underlying the distinct invasion trajectories of the co-vectored pathogens remain unresolved. Our approach allowed us to estimate the unobserved ecological processes underlying pathogen spread while accounting for imperfect detection of human cases. Our model predicts that tick-borne diseases spread in a diffusion-like manner with occasional long-distance dispersal and that babesiosis spread exhibits strong dependence on Lyme disease.

  View details for DOI 10.1098/rspb.2016.0834

  View details for Web of Science ID 000378318700023

  View details for PubMedID 27252022

• PROBING THE GENOMIC DIVERSITY OF THE TICK-BORNE PATHOGEN, BABESIA MICROTI Carpi, G., Walter, K. S., Ben Mamoun, C., Krause, P., Caccone, A., Diuk-Wasser, M. AMER SOC TROP MED & HYGIENE. 2015: 163

  View details for Web of Science ID 000412844102287

• Whole genome capture of vector-borne pathogens from mixed DNA samples: a case study of Borrelia burgdorferi BMC GENOMICS Carpi, G., Walter, K. S., Bent, S. J., Hoen, A. G., Diuk-Wasser, M., Caccone, A. 2015; 16

  Abstract

  Rapid and accurate retrieval of whole genome sequences of human pathogens from disease vectors or animal reservoirs will enable fine-resolution studies of pathogen epidemiological and evolutionary dynamics. However, next generation sequencing technologies have not yet been fully harnessed for the study of vector-borne and zoonotic pathogens, due to the difficulty of obtaining high-quality pathogen sequence data directly from field specimens with a high ratio of host to pathogen DNA.We addressed this challenge by using custom probes for multiplexed hybrid capture to enrich for and sequence 30 Borrelia burgdorferi genomes from field samples of its arthropod vector. Hybrid capture enabled sequencing of nearly the complete genome (~99.5 %) of the Borrelia burgdorferi pathogen with 132-fold coverage, and identification of up to 12,291 single nucleotide polymorphisms per genome.The proprosed culture-independent method enables efficient whole genome capture and sequencing of pathogens directly from arthropod vectors, thus making population genomic study of vector-borne and zoonotic infectious diseases economically feasible and scalable. Furthermore, given the similarities of invertebrate field specimens to other mixed DNA templates characterized by a high ratio of host to pathogen DNA, we discuss the potential applicabilty of hybrid capture for genomic study across diverse study systems.

  View details for DOI 10.1186/s12864-015-1634-x

  View details for Web of Science ID 000355967000001

  View details for PubMedID 26048573

• Microhabitat Partitioning of Aedes simpsoni (Diptera: Culicidae) JOURNAL OF MEDICAL ENTOMOLOGY Walter, K. S., Brown, J. E., Powell, J. R. 2014; 51 (3): 596-604

  Abstract

  Yellow fever virus is a reemerging infection responsible for widespread, sporadic outbreaks across Africa. Although Aedes aegypti (L.) is the most important vector globally, in East Africa, epidemics may be vectored by Aedes bromeliae (Theobald), a member of the Aedes simpsoni (Theobald) species complex. The Ae. simpsoni complex contains 10 subspecies, of which Ae. bromeliae alone has been incriminated as a vector of yellow fever virus. However, morphological markers cannot distinguish Ae. bromeliae from conspecifics, including the sympatric and non-anthropophilic Aedes lilii (Theobald). Here, we used three sequenced nuclear markers to examine the population structure of Ae. simpsoni complex mosquitoes collected from diverse habitats in Rabai, Kenya. Gene trees consistently show strong support for the existence of two clades in Rabai, with segregation by habitat. Domestic mosquitoes segregate separately from forest-collected mosquitoes, providing evidence of habitat partitioning on a small spatial scale (< 5 km). Although speculative, these likely represent what have been described as Ae. bromeliae and Ae. lilii, respectively. The observation of high levels of diversity within Rabai indicates that this species complex may exhibit significant genetic differentiation across East Africa. The genetic structure, ecology, and range of this important disease vector are surprisingly understudied and need to be further characterized.

  View details for DOI 10.1603/ME13097

  View details for Web of Science ID 000335660900013

  View details for PubMedID 24897852

• HLA Class I Subtype-Dependent Expansion of KIR3DS1(+) and KIR3DL1(+) NK Cells during Acute Human Immunodeficiency Virus Type 1 Infection JOURNAL OF VIROLOGY Alter, G., Rihn, S., Walter, K., Nolting, A., Martin, M., Rosenberg, E. S., Miller, J. S., Carrington, M., Altfeld, M. 2009; 83 (13): 6798-6805

  Abstract

  NK cells are critical in the early containment of viral infections. Epidemiological and functional studies have shown an important role of NK cells expressing specific killer immunoglobulin-like receptors (KIRs) in the control of human immunodeficiency virus type 1 (HIV-1) infection, but little is known about the mechanisms that determine the expansion of these antiviral NK cell populations during acute HIV-1 infection. Here we demonstrate that NK cells expressing the activating receptor KIR3DS1(+) and, to a lesser extent, the inhibitory receptor KIR3DL1(+) specifically expand in acute HIV-1 infection in the presence of HLA-B Bw480I, the putative HLA class I ligand for KIR3DL1/3DS1. These data demonstrate for the first time the HLA class I subtype-dependent expansion of specific KIR(+) NK cells during an acute viral infection in humans.

  View details for DOI 10.1128/JVI.00256-09

  View details for Web of Science ID 000267354100046

  View details for PubMedID 19386717

  View details for PubMedCentralID PMC2698561