A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available

Host tropism determination by convergent evolution of immunological evasion in the Lyme disease system

Pathogens possess the ability to adapt and survive in some host species but not in others-an ecological trait known as host tropism. Transmitted through ticks and carried mainly by mammals and birds, the Lyme disease (LD) bacterium is a well-suited model to study such tropism. Three main causative agents of LD, Borrelia burgdorferi, B. afzelii, and B. garinii, vary in host ranges through mechanisms eluding characterization. By feeding ticks infected with different Borrelia species, utilizing feeding chambers and live mice and quail, we found species-level differences in bacterial transmission. These differences localize on the tick blood meal, and specifically complement, a defense in vertebrate blood, and a polymorphic bacterial protein, CspA, which inactivates complement by binding to a host complement inhibitor, Factor H (FH). CspA selectively confers bacterial transmission to vertebrates that produce FH capable of allele-specific recognition. CspA is the only member of the Pfam54 gene family to exhibit host-specific FH-binding. Phylogenetic analyses revealed convergent evolution as the driver of such uniqueness, and that FH-binding likely emerged during the last glacial maximum. Our results identify a determinant of host tropism in Lyme disease infection, thus defining an evolutionary mechanism that shapes host-pathogen associations

High Heritability Is Compatible with the Broad Distribution of Set Point Viral Load in HIV Carriers.

Set point viral load in HIV patients ranges over several orders of magnitude and is a key determinant of disease progression in HIV. A number of recent studies have reported high heritability of set point viral load implying that viral genetic factors contribute substantially to the overall variation in viral load. The high heritability is surprising given the diversity of host factors associated with controlling viral infection. Here we develop an analytical model that describes the temporal changes of the distribution of set point viral load as a function of heritability. This model shows that high heritability is the most parsimonious explanation for the observed variance of set point viral load. Our results thus not only reinforce the credibility of previous estimates of heritability but also shed new light onto mechanisms of viral pathogenesis

Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting

Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such largescale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1

Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization

Lung granulomas are the pathologic hallmark of tuberculosis (TB). T cells are a major cellular component of TB lung granulomas and are known to play an important role in containment of Mycobacterium tuberculosis (Mtb) infection. We used cynomolgus macaques, a non-human primate model that recapitulates human TB with clinically active disease, latent infection or early infection, to understand functional characteristics and dynamics of T cells in individual granulomas. We sought to correlate T cell cytokine response and bacterial burden of each granuloma, as well as granuloma and systemic responses in individual animals. Our results support that each granuloma within an individual host is independent with respect to total cell numbers, proportion of T cells, pattern of cytokine response, and bacterial burden. The spectrum of these components overlaps greatly amongst animals with different clinical status, indicating that a diversity of granulomas exists within an individual host. On average only about 8% of T cells from granulomas respond with cytokine production after stimulation with Mtb specific antigens, and few “multi-functional” T cells were observed. However, granulomas were found to be “multi-functional” with respect to the combinations of functional T cells that were identified among lesions from individual animals. Although the responses generally overlapped, sterile granulomas had modestly higher frequencies of T cells making IL-17, TNF and any of T-1 (IFN-γ, IL-2, or TNF) and/or T-17 (IL-17) cytokines than non-sterile granulomas. An inverse correlation was observed between bacterial burden with TNF and T-1/T-17 responses in individual granulomas, and a combinatorial analysis of pair-wise cytokine responses indicated that granulomas with T cells producing both pro- and anti-inflammatory cytokines (e.g. IL-10 and IL-17) were associated with clearance of Mtb. Preliminary evaluation suggests that systemic responses in the blood do not accurately reflect local T cell responses within granulomas

Whole genome analysis of extensively drug resistant Mycobacterium tuberculosis strains in Peru

Peru has the highest burden of multidrug-resistant tuberculosis in the Americas region. Since 1999, the annual number of extensively drug-resistant tuberculosis (XDR-TB) Peruvian cases has been increasing, becoming a public health challenge. The objective of this study was to perform genomic characterization of Mycobacterium tuberculosis strains obtained from Peruvian patients with XDR-TB diagnosed from 2011 to 2015 in Peru. Whole genome sequencing (WGS) was performed on 68 XDR-TB strains from different regions of Peru. 58 (85.3%) strains came from the most populated districts of Lima and Callao. Concerning the lineages, 62 (91.2%) strains belonged to the Euro-American Lineage, while the remaining 6 (8.8%) strains belonged to the East-Asian Lineage. Most strains (90%) had high-confidence resistance mutations according to pre-established WHO-confident grading system. Discordant results between microbiological and molecular methodologies were caused by mutations outside the hotspot regions analysed by commercial molecular assays (rpoB I491F and inhA S94A). Cluster analysis using a cut-off ≤ 10 SNPs revealed that only 23 (34%) strains evidenced recent transmission links. This study highlights the relevance and utility of WGS as a high-resolution approach to predict drug resistance, analyse transmission of strains between groups, and determine evolutionary patterns of circulating XDR-TB strains in the country.Revisión por pare

Multi-scale immune selection and the maintenance of structured antigenic diversity in the malaria parasite Plasmodium falciparum

The most virulent malaria parasite, Plasmodium falciparum, makes use of extensive antigenic diversity to maximise its transmission potential. Parasite genomes contain several highly polymorphic gene families, whose products are the target of protective immune responses. The best studied of these are the PfEMP1 surface proteins, which are encoded by the var multi-gene family and are important virulence factors. During infection, the parasite switches expression between PfEMP1 variants in order to evade adaptive immune responses and prolong infection. On the population level, parasites appear to be structured with respect to their var genes into non-overlapping repertoires, which can lead to high reinfection rates. This non-random structuring of antigenic diversity can also be found at the level of individual var gene repertoires and var genes themselves. However, not much is known about the evolutionary determinants which select for and maintain this structure at different ecological scales. In this thesis I investigate the mechanisms by which multi-scale immune selection and other ecological factors influence the evolution of structured diversity. Using a suite of theoretical frameworks I show that treating diversity as a dynamic property, which emerges from the underlying infection and transmission processes, has a major effect on the relationship between the parasite’s transmis- sion potential and disease prevalence, with important implications for monitoring control efforts. Furthermore, I show that an evolutionary trade-off between within-host and between-host fitness together with functional constraints on diversification can explain the structured diversity found at both the repertoire and parasite population level and might also account for empirically observed exposure-dependent acquisition of immunity. Together, this work highlights the need to consider evolutionary factors acting at different ecological scales to gain a more comprehensive understanding of the complex immune-epidemiology of P. falciparum malaria

Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization

Lung granulomas are the pathologic hallmark of tuberculosis (TB). T cells are a major cellular component of TB lung granulomas and are known to play an important role in containment of Mycobacterium tuberculosis (Mtb) infection. We used cynomolgus macaques, a non-human primate model that recapitulates human TB with clinically active disease, latent infection or early infection, to understand functional characteristics and dynamics of T cells in individual granulomas. We sought to correlate T cell cytokine response and bacterial burden of each granuloma, as well as granuloma and systemic responses in individual animals. Our results support that each granuloma within an individual host is independent with respect to total cell numbers, proportion of T cells, pattern of cytokine response, and bacterial burden. The spectrum of these components overlaps greatly amongst animals with different clinical status, indicating that a diversity of granulomas exists within an individual host. On average only about 8% of T cells from granulomas respond with cytokine production after stimulation with Mtb specific antigens, and few “multi-functional” T cells were observed. However, granulomas were found to be “multi-functional” with respect to the combinations of functional T cells that were identified among lesions from individual animals. Although the responses generally overlapped, sterile granulomas had modestly higher frequencies of T cells making IL-17, TNF and any of T-1 (IFN-γ, IL-2, or TNF) and/or T-17 (IL-17) cytokines than non-sterile granulomas. An inverse correlation was observed between bacterial burden with TNF and T-1/T-17 responses in individual granulomas, and a combinatorial analysis of pair-wise cytokine responses indicated that granulomas with T cells producing both pro- and anti-inflammatory cytokines (e.g. IL-10 and IL-17) were associated with clearance of Mtb. Preliminary evaluation suggests that systemic responses in the blood do not accurately reflect local T cell responses within granulomas