Adrian Veres

Quantitative Analysis of Culture Using Millions of Digitized Books

Linguistic and cultural changes are revealed through the analyses of words appearing in books. We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of ‘culturomics,’ focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.

Single-cell barcoding and sequencing using droplet microfluidics

Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.

Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes.

Predicting evolutionary paths to antibiotic resistance is key for understanding and controlling drug resistance. When considering a single final resistant genotype, epistatic contingencies among mutations restrict evolution to a small number of adaptive paths. Less attention has been given to multi-peak landscapes, and while specific peaks can be favoured, it is unknown whether and how early a commitment to final fate is made. Here we characterize a multi-peaked adaptive landscape for trimethoprim resistance by constructing all combinatorial alleles of seven resistance-conferring mutations in dihydrofolate reductase. We observe that epistatic interactions increase rather than decrease the accessibility of each peak; while they restrict the number of direct paths, they generate more indirect paths, where mutations are adaptively gained and later adaptively lost or changed. This enhanced accessibility allows evolution to proceed through many adaptive steps while delaying commitment to genotypic fate, hindering our ability to predict or control evolutionary outcomes.

An Augmented SMS Intervention to Improve Access to Antenatal CD4 Testing and ART Initiation in HIV-Infected Pregnant Women: A Cluster Randomized Trial

Background Less than one-third of HIV-infected pregnant women eligible for combination antiretroviral therapy (ART) globally initiate treatment prior to delivery, with lack of access to timely CD4 results being a principal barrier. We evaluated the effectiveness of an SMS-based intervention to improve access to timely antenatal ART. Methods We conducted a stepped-wedge cluster randomized trial of a low-cost programmatic intervention in 20 antenatal clinics in Gaborone, Botswana. From July 2011-April 2012, 2 clinics were randomly selected every 4 weeks to receive an ongoing clinic-based educational intervention to improve CD4 collection and to receive CD4 results via an automated SMS platform with active patient tracing. CD4 testing before 26 weeks gestation and ART initiation before 30 weeks gestation were assessed. Results Three-hundred-sixty-six ART-naïve women were included, 189 registering for antenatal care under Intervention and 177 under Usual Care periods. Of CD4-eligible women, 100 (59.2%) women under Intervention and 79 (50.6%) women under Usual Care completed CD4 phlebotomy before 26 weeks gestation, adjusted odds ratio (aOR, adjusted for time that a clinic initiated Intervention) 0.87 (95% confidence interval [CI]0.47–1.63, P = 0.67). The SMS-based platform reduced time to clinic receipt of CD4 test result from median of 16 to 6 days (P<0.001), was appreciated by clinic staff, and was associated with reduced operational cost. However, rates of ART initiation remained low, with 56 (36.4%) women registering under Intervention versus 37 (24.2%) women under Usual Care initiating ART prior to 30 weeks gestation, aOR 1.06 (95%CI 0.53–2.13, P = 0.87). Conclusions The augmented SMS-based intervention delivered CD4 results more rapidly and efficiently, and this type of SMS-based results delivery platform may be useful for a variety of tests and settings. However, the intervention did not appear to improve access to timely antenatal CD4 testing or ART initiation, as obstacles other than CD4 impeded ART initiation during pregnancy.

Identifying Gene Expression Programs of Cell-type Identity and Cellular Activity with Single-Cell RNA-Seq

Identifying gene expression programs underlying cell-type identity and cellular processes is a crucial step toward understanding the organization of cells and tissues. Although single-cell RNA-Seq (scRNA-Seq) can quantify transcripts in individual cells, each cell’s expression may derive both from programs determining cell-type and from programs facilitating dynamic cellular activities such as cell-division or apoptosis, which cannot be easily disentangled with current methods. Here, we introduce clustered nonnegative matrix factorization (cNMF) as a solution to this problem. We show with simulations that it deconvolutes scRNA-Seq profiles into interpretable programs corresponding to both cell-types and cellular activities. Applied to published brain organoid and visual cortex datasets, cNMF refines the hierarchy of cell-types and identifies both expected (e.g. cell-cycle and hypoxia) and intriguing novel activity programs. In summary, we show that cNMF can increase the accuracy of cell-type identification while simultaneously inferring interpretable cellular activity programs in scRNA-Seq data, thus providing useful insight into how cells vary dynamically within cell-types.

Population diversity jeopardizes the efficacy of antibiotic cycling

Treatment strategies that anticipate and respond to the evolution of pathogens are promising tools for combating the global rise of antibiotic resistance1–3. Mutations conferring resistance to one drug can confer positive or negative cross-resistance to other drugs4. The sequential use of drugs exhibiting negative cross-resistance has been proposed to prevent or slow down the evolution of resistance5–8, although factors affecting its efficacy have not been investigated. Here we show that population diversity can disrupt the efficacy of negative cross-resistance-based therapies. By testing 3317 resistant Staphylococcus aureus mutants against multiple antibiotics, we show that first-step mutants exhibit diverse cross-resistance profiles: even when the majority of mutants show negative cross-resistance, rare positive cross-resistant mutants can appear. Using a drug pair showing reciprocal negative cross-resistance, we found that selection for resistance to the first drug in small populations can decrease resistance to the second drug, but identical selection conditions in large populations can increases resistance to the second drug through the appearance of rare positive cross-resistant mutants. We further find that, even with small populations and strong bottlenecks, resistance to both drugs can increase through sequential steps of negative cross-resistance cycling. Thus, low diversity is necessary but not sufficient for effective cycling therapies. While evolutionary interventions are promising tools for controlling antibiotic resistance, they can be sensitive to population diversity and the accessibility of evolutionary paths, and so must be carefully designed to avoid harmful outcomes.