Exploring the Plasmodium falciparum Transcriptome Using Hypergeometric Analysis of Time Series (HATS)

Malaria poses a significant public health and economic threat in many regions of the world, disproportionately affecting children in sub-Saharan Africa under the age of five. Though success has been celebrated in lowering infection rates, it remains a serious challenge, causing at least 200 million infections and 655,000 deaths per year, with deleterious effects on economic growth and development. Investigation of the malaria parasite Plasmodium falciparum has entered the post-genomics age, with several strains sequenced and many microarray gene expression studies performed. Gene expression studies allow a full sampling of the genomic repertoire of a parasite, and their detailed analysis will prove invaluable in deciphering novel parasite biology as well as the modes of action of antimalarial drug resistance. We have developed a computational pipeline that converts a series of fluorescence readings from a DNA microarray into a meaningful set of biological hypotheses based on the comparison of two lines, generally one that is drug sensitive and one that is drug resistant. Each step of the computational pipeline is described in detail in this thesis, beginning with data normalization and alignment, followed by visualization through dimensionality reduction, and finally a direct analysis of the differences and similarities between the two lines. Comparisons and analyses were performed at both the individual gene and gene set level. An important component of the analytical methods we have developed is a suite of visualization tools that help to easily identify outliers and experimental flaws, measure the significance of predictions, show how lines relate and how well they can be aligned, and demonstrate the results of an analysis. These visualization tools should be used as a starting point for further biological study to test the resulting hypotheses. We also developed a software tool, Gene Attribute and Set Enrichment Ranking (GASER), which combines a wealth of genomic data from the TDR Targets web site along with expression data from a variety of sources, and allows researchers to create sophisticated weighted queries to undercover potential drug targets. Queries in our system can be updated in real time, along with their accompanying gene and gene set lists. We analyzed all possible pair-wise combinations of 11 parasite lines to create baseline distributions for gene and gene set enrichment. Using the baseline as a comparison, we identified and discarded spurious results and recognized stochastic genes and gene sets. We analyzed three major sets of parasite lines: those involving manipulation of the multidrug resistance-1 (PfMDR1) transporter, a key resistance determinant; those involving manipulation of the P. falciparum chloroquine resistance transporter (PfCRT), another important resistance determinant; and finally a set of parasites that had varying sensitivity to artemisinins. This analysis resulted in a rich library of high scoring genes that may merit further exploration as potential modes of action of resistance. More specifically, we found that manipulation of pfcrt expression resulted in an up-regulation of tRNA synthetases, which might serve to increase protein production in response to reduced amino acid availability from degraded hemoglobin. We observed that a copy number increase in pfmdr1 resulted in increases in glycerophospholipid metabolism and up-regulation of a number of ABC transporters. Finally, when comparing artemisinin sensitive to artemisinin tolerant lines, we found an increased abundance of redox metabolites and the transcripts involved in redox regulation, and significant reduction in transcription and altered expression of transcripts encoding for core histone proteins. These alterations could help confer an increased tolerance to drug induced redox perturbation by lowering endogenous redox stress. We also offer a robust computational tool, Hypergeometric Analysis of Time Series (HATS), to handle challenging biological questions related to comparison of time series experiments. Our pipeline provides a rigorous method for aligning expression experiments and then determining which genes and gene sets differ most between them. The changes in gene expression level between drug-sensitive and drug-resistant lines offer important clues in our quest for understanding mechanisms of resistance and identifying new drug targets. Our pipeline allows for comparison of future lines with our base set and holds potential for other organisms, especially those similar to Plasmodium with a strong time-dependent component. The full excel files of all the analyses performed in this thesis can be found at: (http://www.fidock.org/dan)

A Field Trip That’s Not About the Destination but the Journey

This Practitioner Perspective presents a middle school unit focused on designing a day-long field trip as an effective project-based initiative for advancing social and emotional learning (SEL). It considers the social and emotional competencies students develop as they navigate the complexities of this project: researching options, planning an itinerary that meets various parameters, and ultimately taking the trip. It also offers practical guidance to schools for successfully adopting this program

A Self-Organized Method for Computing the Epidemic Threshold in Computer Networks

In many cases, tainted information in a computer network can spread in a way similar to an epidemics in the human world. On the other had, information processing paths are often redundant, so a single infection occurrence can be easily "reabsorbed". Randomly checking the information with a central server is equivalent to lowering the infection probability but with a certain cost (for instance processing time), so it is important to quickly evaluate the epidemic threshold for each node. We present a method for getting such information without resorting to repeated simulations. As for human epidemics, the local information about the infection level (risk perception) can be an important factor, and we show that our method can be applied to this case, too. Finally, when the process to be monitored is more complex and includes "disruptive interference", one has to use actual simulations, which however can be carried out "in parallel" for many possible infection probabilities

Twittering on about mental health: is it worth the effort?

The medical community disseminates information increasingly using social media. Randomised controlled trials are being conducted in this area to evaluate effectiveness of social media with mixed results so far, but more trials are likely to be published in the coming years. One recent twitter randomised control trial using Cochrane Schizophrenia Group reviews suggests that tweets increase the hits to the target web page by about threefold and time spent on the web page is also increased threefold when referrals come in via twitter. These are early findings and need further replication. Twitter appeals to professionals, entertainers and politicians among others as a means of networking with peers and connecting with the wider public. Twitter, in particular, seems to be well placed for use by the medical community and is effective in promoting messages, updating information, interacting with each other locally and internationally and more so during conferences. Twitter is also increasingly used to disseminate evidence in addition to traditional media such as academic peer-reviewed journals. Caution is required using twitter as inadvertent tweets can lead to censure. Overall, the use of twitter responsibly by the medical community will increase visibility of research findings and ensure up to date evidence is readily accessible. This should open the door for further trials of different social media platforms to evaluate their effectiveness in disseminating accurate high-quality information instantaneously to a global audience

Genome-wide transcriptome profiling reveals functional networks involving the Plasmodium falciparum drug resistance transporters PfCRT and PfMDR1

Background The acquisition of multidrug resistance by Plasmodium falciparum underscores the need to understand the underlying molecular mechanisms so as to counter their impact on malaria control. For the many antimalarials whose mode of action relates to inhibition of heme detoxification inside infected erythrocytes, the digestive vacuole transporters PfCRT and PfMDR1 constitute primary resistance determinants. Results Using gene expression microarrays over the course of the parasite intra-erythrocytic developmental cycle, we compared the transcriptomic profiles between P. falciparum strains displaying mutant or wild-type pfcrt or varying in pfcrt or pfmdr1 expression levels. To account for differences in the time of sampling, we developed a computational method termed Hypergeometric Analysis of Time Series, which combines Fast Fourier Transform with a modified Gene Set Enrichment Analysis. Our analysis revealed coordinated changes in genes involved in protein catabolism, translation initiation and DNA/RNA metabolism. We also observed differential expression of genes with a role in transport or coding for components of the digestive vacuole. Interestingly, a global comparison of all profiled transcriptomes uncovered a tight correlation between the transcript levels of pfcrt and pfmdr1, extending to dozens of other genes, suggesting an intricate regulatory balance in order to maintain optimal physiological processes. Conclusions This study provides insight into the mechanisms by which P. falciparum adjusts to the acquisition of mutations or gene amplification in key transporter loci that mediate drug resistance. Our results implicate several biological pathways that may be differentially regulated to compensate for impaired transporter function and alterations in parasite vacuole physiology

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Study protocol : responding to the needs of patients with IgA nephropathy, a social media approach

Background IgA nephropathy is the most common cause of glomerulonephritis in the Western world and predominantly affects young adults. Demographically these patients are the biggest users of social media. With increasing numbers of patients turning to social media to seek information and support in dealing with their disease, analysis of social media streams is an attractive modern strategy for understanding and responding to unmet patient need. Methods To identify unmet patient need in this population, a framework analysis will be undertaken of prospectively acquired social media posts from patients with IgA nephropathy, acquired from a range of different social media platforms. In collaboration with patients and members of the clinical multidisciplinary team, resources will be created to bridge gaps in patient knowledge and education identified through social media analysis and returned to patients via social media channels and bespoke websites. Analysis of the impact of these resources will be undertaken with further social media analysis, surveys and focus groups. Conclusions Patients with chronic diseases are increasingly using social networking channels to connect with others with similar diseases and to search for information to help them understand their condition. This project is a 21st century digital solution to understanding patient need and developing resources in partnership with patients, and has wide applicability as a future model for understanding patient needs in a variety of conditions

Systematic review on the prevalence, frequency and comparative value of adverse events data in social media

Aim: The aim of this review was to summarize the prevalence, frequency and comparative value of information on the adverse events of healthcare interventions from user comments and videos in social media. Methods: A systematic review of assessments of the prevalence or type of information on adverse events in social media was undertaken. Sixteen databases and two internet search engines were searched in addition to handsearching, reference checking and contacting experts. The results were sifted independently by two researchers. Data extraction and quality assessment were carried out by one researcher and checked by a second. The quality assessment tool was devised in-house and a narrative synthesis of the results followed. Results: From 3064 records, 51 studies met the inclusion criteria. The studies assessed over 174 social media sites with discussion forums (71%) being the most popular. The overall prevalence of adverse events reports in social media varied from 0.2% to 8% of posts. Twenty-nine studies compared the results from searching social media with using other data sources to identify adverse events. There was general agreement that a higher frequency of adverse events was found in social media and that this was particularly true for ‘symptom’ related and ‘mild’ adverse events. Those adverse events that were under-represented in social media were laboratory-based and serious adverse events. Conclusions: Reports of adverse events are identifiable within social media. However, there is considerable heterogeneity in the frequency and type of events reported, and the reliability or validity of the data has not been thoroughly evaluated

Tweeting the Meeting: An In-Depth Analysis of Twitter Activity at Kidney Week 2011

In recent years, the American Society of Nephrology (ASN) has increased its efforts to use its annual conference to inform and educate the public about kidney disease. Social media, including Twitter, has been one method used by the Society to accomplish this goal. Twitter is a popular microblogging service that serves as a potent tool for disseminating information. It allows for short messages (140 characters) to be composed by any author and distributes those messages globally and quickly. The dissemination of information is necessary if Twitter is to be considered a tool that can increase public awareness of kidney disease. We hypothesized that content, citation, and sentiment analyses of tweets generated from Kidney Week 2011 would reveal a large number of educational tweets that were disseminated to the public. An ideal tweet for accomplishing this goal would include three key features: 1) informative content, 2) internal citations, and 3) positive sentiment score. Informative content was found in 29% of messages, greater than that found in a similarly sized medical conference (2011 ADA Conference, 16%). Informative tweets were more likely to be internally, rather than externally, cited (38% versus 22%, p<0.0001), thereby amplifying the original information to an even larger audience. Informative tweets had more negative sentiment scores than uninformative tweets (means −0.162 versus 0.199 respectively, p<0.0001), therefore amplifying a tweet whose content had a negative tone. Our investigation highlights significant areas of promise and improvement in using Twitter to disseminate medical information in nephrology from a scientific conference. This goal is pertinent to many nephrology-focused conferences that wish to increase public awareness of kidney disease