J C Sanz

Effects of delayed recovery and nonuniform transmission on the spreading of diseases in complex networks

Abstract We investigate the effects of delaying the time to recovery (delayed recovery) and of nonuniform transmission on the propagation of diseases on structured populations. Through a mean-field approximation and large-scale numerical simulations, we find that postponing the transition from the infectious to the recovered states can largely reduce the epidemic threshold, therefore promoting the outbreak of epidemics. On the other hand, if we consider nonuniform transmission among individuals, the epidemic threshold increases, thus inhibiting the spreading process. When both mechanisms are at work, the latter might prevail, hence resulting in an increase of the epidemic threshold with respect to the standard case, in which both ingredients are absent. Our findings are of interest for a better understanding of how diseases propagate on structured populations and to a further design of efficient immunization strategies.

The Transcriptional Regulatory Network of Mycobacterium tuberculosis

Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR) networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network of Mycobacterium tuberculosis (M.tb), which incorporates newly characterized transcriptional regulations coming from 31 recent, different experimental works available in the literature. As a result of the incorporation of these data, the new network doubles the size of previous data collections, incorporating more than a third of the entire genome of the bacterium. We also present an exhaustive topological analysis of the new assembled network, focusing on the statistical characterization of motifs significances and the comparison with other model organisms. The expanded M.tb transcriptional regulatory network, considering its volume and completeness, constitutes an important resource for diverse tasks such as dynamic modeling of gene expression and signaling processes, computational reliability determination or protein function prediction, being the latter of particular relevance, given that the function of only a small percent of the proteins of M.tb is known.

Social status alters immune regulation and response to infection in macaques

Status alters immune function in macaques Rhesus macaques experience variable levels of stress on the basis of their position in the social hierarchy. To examine how stress affects immune function, Snyder-Mackler et al. manipulated the social status of individual macaques (see the Perspective by Sapolsky). Social status influenced the immune system at multiple levels, from immune cell numbers to gene expression, and altered signaling pathways in a model of response to infection. Macaques possess a plastic and adaptive immune response wherein social subordination promotes antibacterial responses, whereas high social status promotes antiviral responses. Science, this issue p. 1041; see also p. 967 Manipulation of social status in macaques affects cell-specific immune gene regulation. Social status is one of the strongest predictors of human disease risk and mortality, and it also influences Darwinian fitness in social mammals more generally. To understand the biological basis of these effects, we combined genomics with a social status manipulation in female rhesus macaques to investigate how status alters immune function. We demonstrate causal but largely plastic social status effects on immune cell proportions, cell type–specific gene expression levels, and the gene expression response to immune challenge. Further, we identify specific transcription factor signaling pathways that explain these differences, including low-status–associated polarization of the Toll-like receptor 4 signaling pathway toward a proinflammatory response. Our findings provide insight into the direct biological effects of social inequality on immune function, thus improving our understanding of social gradients in health.

New features of rubella in Spain: the evidence of an outbreak.

In most of western Europe the rubella vaccine coverage is high. However, prior to the introduction of the vaccine in Latin America, rubella susceptibility in women of childbearing age was 10-25%. Forty one (93%) countries in Latin America have adopted the rubella vaccine since 2002. The adult immigrant population in Spain constitutes a group of susceptibles. In February 2003, the Madrid Community Measles Elimination Plan detected an increase in rubella notifications in women who had been born in Latin America. A descriptive study was undertaken to characterise the outbreak. A confirmed case was a person with fever or rash and a positive IgM serology, and living in Madrid, between 1 December 2002 and 31 March 2003. The secondary attack rate (SAR) per household was calculated. A total of 19 cases of rubella were identified, 15 were confirmed and 4 were probable cases. Fourteen (73.7%) cases were women at childbearing age. The mean age was 25.1 years. One pregnancy was diagnosed with a voluntary termination. Eleven (57.9%) cases were from Ecuador. The mean time of residence in Spain was 41 months. None of the cases or the 54 (78.3%) household contacts had been vaccinated against rubella. The SAR was 9.1%. This study showed the spread of rubella in the susceptible Latin American Community that is resident in Madrid. The interventions proposed were a vaccination programme towards immigrants, a health education campaign to prevent congenital rubella, and a health professional training programme case management.

Late detection of a shigellosis outbreak in a school in Madrid.

Even though shigellosis in Spain is rare, an indigenous outbreak is occasionally detected. We describe an outbreak in a school in Madrid caused by person-to-person transmission of Shigella sonnei. After the detection of Shigella sonnei in a stool sample from a 3 year old girl, an investigation at her school was initiated. Questionnaires were distributed to the parents of 520 pupils attending the school. A case was defined as a school case if it was the first case in a childs household, and as a household case if other members of the household had fallen ill first. We identified 88 cases (60 pupils and 28 of their family members). The attack rate (AR) was 12% in the school and 32% in the families. There was a significant association between higher AR and lower age. The outbreak lasted for two months. The length and the shape of the epidemic curve of the 60 cases in pupils suggests person-to-person transmission. Shigella sonnei isolated from 5 different cases were typed by pulsed field gel electrophoresis (PFGE) and was found to be an identical strain. The prolonged duration of the outbreak was probably due to delayed detection, and stopped as soon as control measures were introduced.

On the impact of masking and blocking hypotheses for measuring the efficacy of new tuberculosis vaccines.

Over the past 60 years, the Mycobacterium bovis bacille Calmette–Guérin (BCG) has been used worldwide to prevent tuberculosis (TB). However, BCG has shown a very variable efficacy in different trials, offering a wide range of protection in adults against pulmonary TB. One of the most accepted hypotheses to explain these inconsistencies points to the existence of a pre-existing immune response to antigens that are common to environmental sources of mycobacterial antigens and Mycobacterium tuberculosis. Specifically, two different mechanisms have been hypothesized to explain this phenomenon: the masking and the blocking effects. According to masking hypothesis, previous sensitization confers some level of protection against TB that masks vaccine’s effects. In turn, the blocking hypothesis postulates that previous immune response prevents vaccine taking of a new TB vaccine. In this work we introduce a series of models to discriminate between masking and blocking mechanisms and address their relative likelihood. We apply our methodology to the data reported by BCG-REVAC clinical trials, which were specifically designed for studying BCG efficacy variability. Our results yield estimates that are consistent with high levels of blocking (41% in Manaus -95% CI [14–68]- and 96% in Salvador -95% CI [52–100]-). Moreover, we also show that masking does not play any relevant role in modifying vaccine’s efficacy either alone or in addition to blocking. The quantification of these effects around a plausible model constitutes a relevant step towards impact evaluation of novel anti-tuberculosis vaccines, which are susceptible of being affected by similar effects, especially if applied on individuals previously exposed to mycobacterial antigens.

Topological effects of data incompleteness of gene regulatory networks

BackgroundThe topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly.ResultsIn this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different levels.ConclusionsIn doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis.

Social status alters chromatin accessibility and the gene regulatory response to glucocorticoid stimulation in rhesus macaques

Low social status is an important predictor of disease susceptibility and mortality risk in humans and other social mammals. These effects are thought to stem in part from dysregulation of the glucocorticoid (GC)-mediated stress response. However, the molecular mechanisms that connect low social status and GC dysregulation to downstream health outcomes remain elusive. Here, we used an in vitro glucocorticoid challenge to investigate the consequences of experimentally manipulated social status (i.e., dominance rank) for immune cell gene regulation in female rhesus macaques, using paired control and GC-treated peripheral blood mononuclear cell samples. We show that social status not only influences immune cell gene expression, but also chromatin accessibility at hundreds of regions in the genome. Social status effects on gene expression were less pronounced following GC treatment than under control conditions. In contrast, social status effects on chromatin accessibility were stable across conditions, resulting in an attenuated relationship between social status, chromatin accessibility, and gene expression post-GC exposure. Regions that were more accessible in high status animals and regions that become more accessible following GC treatment were enriched for a highly concordant set of transcription factor binding motifs, including motifs for the glucocorticoid receptor co-factor AP-1. Together, our findings support the hypothesis that social status alters the dynamics of GC-mediated gene regulation, and identify chromatin accessibility as a mechanism involved in social stress-driven GC resistance. More broadly, they emphasize the context-dependent nature of social status effects on gene regulation and implicate epigenetic remodeling of chromatin accessibility as a contributing factor.

Genetic and evolutionary determinants of human population variation in immune responses

Humans display remarkable immune response variation when exposed to identical immune challenges. However, our understanding of the genetic, evolutionary, and environmental factors that impact this inter-individual and inter-population immune response heterogeneity is still in its early days. In this review, we discuss three fundamental questions concerning the recent evolution of the human immune system: the degree to which individuals from different populations vary in their innate immune responses, the genetic variants accounting for such differences, and the evolutionary mechanisms that led to the establishment of these variants in modern human populations. We also discuss how past selective events might have contributed to the uneven distribution of immune-related disorders across populations.

Data reliability in complex directed networks

The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimera and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way.