Autonomous Targeting of Infectious Superspreaders Using Engineered Transmissible Therapies

Infectious disease treatments, both pharmaceutical and vaccine, face three universal challenges: the difficulty of targeting treatments to high-risk ‘superspreader’ populations who drive the great majority of disease spread, behavioral barriers in the host population (such as poor compliance and risk disinhibition), and the evolution of pathogen resistance. Here, we describe a proposed intervention that would overcome these challenges by capitalizing upon Therapeutic Interfering Particles (TIPs) that are engineered to replicate conditionally in the presence of the pathogen and spread between individuals — analogous to ‘transmissible immunization’ that occurs with live-attenuated vaccines (but without the potential for reversion to virulence). Building on analyses of HIV field data from sub-Saharan Africa, we construct a multi-scale model, beginning at the single-cell level, to predict the effect of TIPs on individual patient viral loads and ultimately population-level disease prevalence. Our results show that a TIP, engineered with properties based on a recent HIV gene-therapy trial, could stably lower HIV/AIDS prevalence by ∼30-fold within 50 years and could complement current therapies. In contrast, optimistic antiretroviral therapy or vaccination campaigns alone could only lower HIV/AIDS prevalence by <2-fold over 50 years. The TIP's efficacy arises from its exploitation of the same risk factors as the pathogen, allowing it to autonomously penetrate superspreader populations, maintain efficacy despite behavioral disinhibition, and limit viral resistance. While demonstrated here for HIV, the TIP concept could apply broadly to many viral infectious diseases and would represent a new paradigm for disease control, away from pathogen eradication but toward robust disease suppression

Does crop diversity contribute to dietary diversity? Evidence from integration of vegetables into maize-based farming systems

Background: Maize is the most important staple crop for food security and livelihood of smallholder farmers in many parts of sub-Saharan Africa, but it alone cannot ensure food security. Cropping patterns must be diversified to ensure an adequate supply and economic access to greater variety of foods for smallholder farm households. This study measured the effect of crop diversification on household dietary diversity in a selected study locale using a survey of 300 randomly stratified farm households in 10 villages located in the Babati, Kongwa and Kiteto districts of Tanzania. Results: Based on multiple regression analysis, the study found that simply increasing Simpson’s Index does not influence dietary diversity of farm households due to the presence of interaction effect between Simpson’s Index and crop income. It is much more critical and significant to increase the revenue generated from diversified crops along with other socioeconomic endowment and behavioral characteristics of farm households. This is particularly applicable to poorer smallholder farmers who receive crop income less than US$85 per sales transaction and per season. Particularly, marginal and smallholders might be exposed to the effects of crop diversification and crop income toward increasing in their household dietary diversity score. Conclusion: Under average crop income scenarios, households that diversify their crop production tend to increase their dietary diversity from their existing dietary diversity score at a decreasing rate. However, under below average crop income threshold scenarios, farmers tend to increase their dietary diversity score from their existing score at an increasing rate when they diversify into high-value crops that attract relatively high farm gate values and accrue higher net revenues from the market. Monthly food expenditure also tends to positively influence household dietary diversity, indicating that farm households that spend more on market-purchased food have consistent increases in their dietary diversity scores at the household level. This study concludes that improving economic access to variety of foods at the smallholder household level by diversifying diets through increased crop diversification should be encouraged within maize-based farming systems of the study locale, through integration of micronutrient-rich foods such as vegetables

Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.Comment: 35 pages, 6 figures, Submitte

Markers of cerebral damage during delirium in elderly patients with hip fracture

BACKGROUND: S100B protein and Neuron Specific Enolase (NSE) can increase due to brain cell damage and/or increased permeability of the blood-brain-barrier. Elevation of these proteins has been shown after various neurological diseases with cognitive dysfunction. Delirium is characterized by temporal cognitive deficits and is an important risk factor for dementia. The aim of this study was to compare the level of S100B and NSE of patients before, during and after delirium with patients without delirium and investigate the possible associations with different subtypes of delirium. METHODS: The study population were patients aged 65 years or more acutely admitted after hip fracture. Delirium was diagnosed by the Confusion Assessment Method and the subtype by Delirium Symptom interview. In maximal four serum samples per patient S100B and NSE levels were determined by electrochemiluminescence immunoassay. RESULTS: Of 120 included patients with mean age 83.9 years, 62 experienced delirium. Delirious patients had more frequently pre-existing cognitive impairment (67% vs. 18%, p<0.001). Comparing the first samples during delirium to samples of non-delirious patients, a difference was observed in S100B (median 0.16 versus 0.10 ug/L, p=<0.001), but not in NSE (median 11.7 versus 11.7 ng/L, p=0.97). Delirious state (before, during, after) (p<0.001), day of blood withdrawal (p<0.001), pre- or postoperative status (p=0.001) and type of fracture (p=0.036) were all associated with S100B level. The highest S100B levels were found 'during' delirium. S100B levels 'before' and 'after' delirium were still higher than those from 'non-delirious' patients. No significant difference in S100B (p=0.43) or NSE levels (p=0.41) was seen between the hyperactive, hypoactive and mixed subtype of delirium. CONCLUSIONS: Delirium was associated with increased level of S100B which could indicate cerebral damage either due to delirium or leading to delirium. The possible association between higher levels of S100B during delirium and the higher risk of developing dementia after delirium is an interesting field for future research. More studies are needed to elucidate the role of S100B proteins in the pathophysiological pathway leading to delirium and to investigate its possibility as biomarker for deliriu

Genetic Drift of HIV Populations in Culture

Populations of Human Immunodeficiency Virus type 1 (HIV-1) undergo a surprisingly large amount of genetic drift in infected patients despite very large population sizes, which are predicted to be mostly deterministic. Several models have been proposed to explain this phenomenon, but all of them implicitly assume that the process of virus replication itself does not contribute to genetic drift. We developed an assay to measure the amount of genetic drift for HIV populations replicating in cell culture. The assay relies on creation of HIV populations of known size and measurements of variation in frequency of a neutral allele. Using this assay, we show that HIV undergoes approximately ten times more genetic drift than would be expected from its population size, which we defined as the number of infected cells in the culture. We showed that a large portion of the increase in genetic drift is due to non-synchronous infection of target cells. When infections are synchronized, genetic drift for the virus is only 3-fold higher than expected from its population size. Thus, the stochastic nature of biological processes involved in viral replication contributes to increased genetic drift in HIV populations. We propose that appreciation of these effects will allow better understanding of the evolutionary forces acting on HIV in infected patients

Adjusting Phenotypes by Noise Control

Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks

Validation of Self-Reported Health Literacy Questions Among Diverse English and Spanish-Speaking Populations

BackgroundLimited health literacy (HL) contributes to poor health outcomes and disparities, and direct measurement is often time-intensive. Self-reported HL questions have not been validated among Spanish-speaking and diverse English-speaking populations.ObjectiveTo evaluate three self-reported questions: 1 "How confident are you filling out medical forms?"; 2 "How often do you have problems learning about your medical condition because of difficulty understanding written information?"; and 3 "How often do you have someone help you read hospital materials?" Answers were based on a 5-point Likert scale.DesignThis was a validation study nested within a trial of diabetes self-management support in the San Francisco Department of Public Health.ParticipantsEnglish and Spanish-speaking adults with type 2 diabetes receiving primary care.MethodsUsing the Test of Functional Health Literacy in Adults (s-TOFHLA) in English and Spanish as the reference, we classified HL as inadequate, marginal, or adequate. We calculated the C-index and test characteristics of the three questions and summative scale compared to the s-TOFHLA and assessed variations in performance by language, race/ethnicity, age, and education.Key resultsOf 296 participants, 48% were Spanish-speaking; 9% were White, non-Hispanic; 47% had inadequate HL and 12% had marginal HL. Overall, 57% reported being confident with forms "somewhat" or less. The "confident with forms" question performed best for detecting inadequate (C-index = 0.82, (0.77-0.87)) and inadequate plus marginal HL (C index = 0.81, (0.76-0.86); p&lt;0.01 for differences from other questions), and performed comparably to the summative scale. The "confident with forms" question and scale also performed best across language, race/ethnicity, educational attainment, and age.ConclusionsA single self-reported HL question about confidence with forms and a summative scale of three questions discriminated between Spanish and English speakers with adequate HL and those with inadequate and/or inadequate plus marginal HL. The "confident with forms" question or the summative scale may be useful for estimating HL in clinical research involving Spanish-speaking and English-speaking, chronically-ill, diverse populations

HIV Promoter Integration Site Primarily Modulates Transcriptional Burst Size Rather Than Frequency

Mammalian gene expression patterns, and their variability across populations of cells, are regulated by factors specific to each gene in concert with its surrounding cellular and genomic environment. Lentiviruses such as HIV integrate their genomes into semi-random genomic locations in the cells they infect, and the resulting viral gene expression provides a natural system to dissect the contributions of genomic environment to transcriptional regulation. Previously, we showed that expression heterogeneity and its modulation by specific host factors at HIV integration sites are key determinants of infected-cell fate and a possible source of latent infections. Here, we assess the integration context dependence of expression heterogeneity from diverse single integrations of a HIV-promoter/GFP-reporter cassette in Jurkat T-cells. Systematically fitting a stochastic model of gene expression to our data reveals an underlying transcriptional dynamic, by which multiple transcripts are produced during short, infrequent bursts, that quantitatively accounts for the wide, highly skewed protein expression distributions observed in each of our clonal cell populations. Interestingly, we find that the size of transcriptional bursts is the primary systematic covariate over integration sites, varying from a few to tens of transcripts across integration sites, and correlating well with mean expression. In contrast, burst frequencies are scattered about a typical value of several per cell-division time and demonstrate little correlation with the clonal means. This pattern of modulation generates consistently noisy distributions over the sampled integration positions, with large expression variability relative to the mean maintained even for the most productive integrations, and could contribute to specifying heterogeneous, integration-site-dependent viral production patterns in HIV-infected cells. Genomic environment thus emerges as a significant control parameter for gene expression variation that may contribute to structuring mammalian genomes, as well as be exploited for survival by integrating viruses

Cascading signaling pathways improve the fidelity of a stochastically and deterministically simulated molecular RS latch

<p>Abstract</p> <p>Background</p> <p>While biological systems have often been compared with digital systems, they differ by the strong effect of crosstalk between signals due to diffusivity in the medium, reaction kinetics and geometry. Memory elements have allowed the creation of autonomous digital systems and although biological systems have similar properties of autonomy, equivalent memory mechanisms remain elusive. Any such equivalent memory system, however, must silence the effect of crosstalk to maintain memory fidelity.</p> <p>Results</p> <p>Here, we present a system of enzymatic reactions that behaves like an RS latch (a simple memory element in digital systems). Using both a stochastic molecular simulator and ordinary differential equation simulator, we showed that crosstalk between two latches operating in the same spatial localization disrupts the memory fidelity of both latches. Crosstalk was reduced or silenced when simple reaction loops were replaced with multiple step or cascading reactions, showing that cascading signaling pathways are less susceptible to crosstalk.</p> <p>Conclusion</p> <p>Thus, the common biological theme of cascading signaling pathways is advantageous for maintaining the fidelity of a memory latch in the presence of crosstalk. The experimental implementation of such a latch system will lead to novel approaches to cell control using synthetic proteins and will contribute to our understanding of why cells behave differently even when given the same stimulus.</p

Trade-offs and Noise Tolerance in Signal Detection by Genetic Circuits

Genetic circuits can implement elaborated tasks of amplitude or frequency signal detection. What type of constraints could circuits experience in the performance of these tasks, and how are they affected by molecular noise? Here, we consider a simple detection process–a signal acting on a two-component module–to analyze these issues. We show that the presence of a feedback interaction in the detection module imposes a trade-off on amplitude and frequency detection, whose intensity depends on feedback strength. A direct interaction between the signal and the output species, in a type of feed-forward loop architecture, greatly modifies these trade-offs. Indeed, we observe that coherent feed-forward loops can act simultaneously as good frequency and amplitude noise-tolerant detectors. Alternatively, incoherent feed-forward loop structures can work as high-pass filters improving high frequency detection, and reaching noise tolerance by means of noise filtering. Analysis of experimental data from several specific coherent and incoherent feed-forward loops shows that these properties can be realized in a natural context. Overall, our results emphasize the limits imposed by circuit structure on its characteristic stimulus response, the functional plasticity of coherent feed-forward loops, and the seemingly paradoxical advantage of improving signal detection with noisy circuit components