Quantifying online citizen science: Dynamics and demographics of public participation in science.

Citizen scientists around the world are collecting data with their smartphones, performing scientific calculations on their home computers, and analyzing images on online platforms. These online citizen science projects are frequently lauded for their potential to revolutionize the scope and scale of data collection and analysis, improve scientific literacy, and democratize science. Yet, despite the attention online citizen science has attracted, it remains unclear how widespread public participation is, how it has changed over time, and how it is geographically distributed. Importantly, the demographic profile of citizen science participants remains uncertain, and thus to what extent their contributions are helping to democratize science. Here, we present the largest quantitative study of participation in citizen science based on online accounts of more than 14 million participants over two decades. We find that the trend of broad rapid growth in online citizen science participation observed in the early 2000s has since diverged by mode of participation, with consistent growth observed in nature sensing, but a decline seen in crowdsourcing and distributed computing. Most citizen science projects, except for nature sensing, are heavily dominated by men, and the vast majority of participants, male and female, have a background in science. The analysis we present here provides, for the first time, a robust 'baseline' to describe global trends in online citizen science participation. These results highlight current challenges and the future potential of citizen science. Beyond presenting our analysis of the collated data, our work identifies multiple metrics for robust examination of public participation in science and, more generally, online crowds. It also points to the limits of quantitative studies in capturing the personal, societal, and historical significance of citizen science.

Online citizen science with the Zooniverse for analysis of biological volumetric data.

Public participation in research, also known as citizen science, is being increasingly adopted for the analysis of biological volumetric data. Researchers working in this domain are applying online citizen science as a scalable distributed data analysis approach, with recent research demonstrating that non-experts can productively contribute to tasks such as the segmentation of organelles in volume electron microscopy data. This, alongside the growing challenge to rapidly process the large amounts of biological volumetric data now routinely produced, means there is increasing interest within the research community to apply online citizen science for the analysis of data in this context. Here, we synthesise core methodological principles and practices for applying citizen science for analysis of biological volumetric data. We collate and share the knowledge and experience of multiple research teams who have applied online citizen science for the analysis of volumetric biological data using the Zooniverse platform ( www.zooniverse.org ). We hope this provides inspiration and practical guidance regarding how contributor effort via online citizen science may be usefully applied in this domain.

A crowd of BashTheBug volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally, this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, each being present at a pre-determined concentration, thereby determining if the sample isresistant or susceptible to each sample. The minimum inhibitory concentration (MIC) of a drug is the lowestconcentration that inhibits growth and is a more useful quantity but requires each sample to be tested at a range ofconcentrations for each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is still an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

Tuberculosis is a bacterial respiratory infection that kills about 1.4 million people worldwide each year. While antibiotics can cure the condition, the bacterium responsible for this disease, Mycobacterium tuberculosis, is developing resistance to these treatments. Choosing which antibiotics to use to treat the infection more carefully may help to combat the growing threat of drug-resistant bacteria. One way to find the best choice is to test how an antibiotic affects the growth of M. tuberculosis in the laboratory. To speed up this process, laboratories test multiple drugs simultaneously. They do this by growing bacteria on plates with 96 wells and injecting individual antibiotics in to each well at different concentrations. The Comprehensive Resistance Prediction for Tuberculosis (CRyPTIC) consortium has used this approach to collect and analyse bacteria from over 20,000 tuberculosis patients. An image of the 96-well plate is then captured and the level of bacterial growth in each well is assessed by laboratory scientists. But this work is difficult, time-consuming, and subjective, even for tuberculosis experts. Here, Fowler et al. show that enlisting citizen scientists may help speed up this process and reduce errors that arise from analysing such a large dataset. In April 2017, Fowler et al. launched the project 'BashTheBug' on the Zooniverse citizen science platform where anyone can access and analyse the images from the CRyPTIC consortium. They found that a crowd of inexperienced volunteers were able to consistently and accurately measure the concentration of antibiotics necessary to inhibit the growth of M. tuberculosis. If the concentration is above a pre-defined threshold, the bacteria are considered to be resistant to the treatment. A consensus result could be reached by calculating the median value of the classifications provided by as few as 17 different BashTheBug participants. The work of BashTheBug volunteers has reduced errors in the CRyPTIC project data, which has been used for several other studies. For instance, the World Health Organization (WHO) has also used the data to create a catalogue of genetic mutations associated with antibiotics resistance in M. tuberculosis. Enlisting citizen scientists has accelerated research on tuberculosis and may help with other pressing public health concerns.

Deep learning for automatic segmentation of the nuclear envelope in electron microscopy data, trained with volunteer segmentations.

Advancements in volume electron microscopy mean it is now possible to generate thousands of serial images at nanometre resolution overnight, yet the gold standard approach for data analysis remains manual segmentation by an expert microscopist, resulting in a critical research bottleneck. Although some machine learning approaches exist in this domain, we remain far from realizing the aspiration of a highly accurate, yet generic, automated analysis approach, with a major obstacle being lack of sufficient high-quality ground-truth data. To address this, we developed a novel citizen science project, Etch a Cell, to enable volunteers to manually segment the nuclear envelope (NE) of HeLa cells imaged with serial blockface scanning electron microscopy. We present our approach for aggregating multiple volunteer annotations to generate a high-quality consensus segmentation and demonstrate that data produced exclusively by volunteers can be used to train a highly accurate machine learning algorithm for automatic segmentation of the NE, which we share here, in addition to our archived benchmark data.

A Standardized Protocol for Efficient and Reliable Quality Control of Brain Registration in Functional MRI Studies.

Automatic alignment of brain anatomy in a standard space is a key step when processing magnetic resonance imaging for group analyses. Such brain registration is prone to failure, and the results are therefore typically reviewed visually to ensure quality. There is however no standard, validated protocol available to perform this visual quality control (QC). We propose here a standardized QC protocol for brain registration, with minimal training overhead and no required knowledge of brain anatomy. We validated the reliability of three-level QC ratings (OK, Maybe, Fail) across different raters. Nine experts each rated N = 100 validation images, and reached moderate to good agreement (kappa from 0.4 to 0.68, average of 0.54 ± 0.08), with the highest agreement for "Fail" images (Dice from 0.67 to 0.93, average of 0.8 ± 0.06). We then recruited volunteers through the Zooniverse crowdsourcing platform, and extracted a consensus panel rating for both the Zooniverse raters (N = 41) and the expert raters. The agreement between expert and Zooniverse panels was high (kappa = 0.76). Overall, our protocol achieved a good reliability when performing a two level assessment (Fail vs. OK/Maybe) by an individual rater, or aggregating multiple three-level ratings (OK, Maybe, Fail) from a panel of experts (3 minimum) or non-experts (15 minimum). Our brain registration QC protocol will help standardize QC practices across laboratories, improve the consistency of reporting of QC in publications, and will open the way for QC assessment of large datasets which could be used to train automated QC systems.

5-hydroxymethylcytosine is highly dynamic across human fetal brain development.

BACKGROUND: Epigenetic processes play a key role in orchestrating transcriptional regulation during the development of the human central nervous system. We previously described dynamic changes in DNA methylation (5mC) occurring during human fetal brain development, but other epigenetic processes operating during this period have not been extensively explored. Of particular interest is DNA hydroxymethylation (5hmC), a modification that is enriched in the human brain and hypothesized to play an important role in neuronal function, learning and memory. In this study, we quantify 5hmC across the genome of 71 human fetal brain samples spanning 23 to 184 days post-conception. RESULTS: We identify widespread changes in 5hmC occurring during human brain development, notable sex-differences in 5hmC in the fetal brain, and interactions between 5mC and 5hmC at specific sites. Finally, we identify loci where 5hmC in the fetal brain is associated with genetic variation. CONCLUSIONS: This study represents the first systematic analysis of dynamic changes in 5hmC across human neurodevelopment and highlights the potential importance of this modification in the human brain. A searchable database of our fetal brain 5hmC data is available as a resource to the research community at http://www.epigenomicslab.com/online-data-resources .

Rapid Down-Regulation of Glucocorticoid Receptor Gene Expression in the Dentate Gyrus after Acute Stress in vivo: Role of DNA Methylation and MicroRNA Activity.

BACKGROUND: Although glucocorticoid receptors (GRs) in the hippocampus play a vital role in the regulation of physiological and behavioural responses to stress, the regulation of receptor expression remains unclear. This work investigates the molecular mechanisms underpinning stress-induced changes in hippocampal GR mRNA levels in vivo. METHODS: Male Wistar rats were killed either under baseline conditions or after forced swim stress (FSS; 15 min in 25°C water). Rat hippocampi were micro-dissected (for mRNA, microRNA, and DNA methylation analysis) or frozen whole (for chromatin immunoprecipitation). In an additional experiment, rats were pre-treated with RU486 (a GR antagonist) or vehicle. RESULTS: FSS evoked a dentate gyrus-specific reduction in GR mRNA levels. This was related to an increased DNMT3a protein association with a discreet region of the Nr3c1 (GR gene) promoter, shown here to undergo increased DNA methylation after FSS. FSS also caused a time-dependent increase in the expression of miR-124a, a microRNA known to reduce GR mRNA expression, which was inversely correlated with a reduction in GR mRNA levels 30 min after FSS. FSS did not affect GR binding to a putative negative glucocorticoid response element within the Nr3c1 gene. CONCLUSIONS: Acute stress results in decreased GR mRNA expression specifically in the dentate gyrus. Our results indicate that a complex interplay of multiple molecular mechanisms - including increased DNA methylation of discrete CpG residues within the Nr3c1 gene, most likely facilitated by DNMT3a, and increased expression of miR-124a - could be responsible for these changes.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease.

Stress-induced gene expression and behavior are controlled by DNA methylation and methyl donor availability in the dentate gyrus.

Stressful events evoke long-term changes in behavioral responses; however, the underlying mechanisms in the brain are not well understood. Previous work has shown that epigenetic changes and immediate-early gene (IEG) induction in stress-activated dentate gyrus (DG) granule neurons play a crucial role in these behavioral responses. Here, we show that an acute stressful challenge [i.e., forced swimming (FS)] results in DNA demethylation at specific CpG (5'-cytosine-phosphate-guanine-3') sites close to the c-Fos (FBJ murine osteosarcoma viral oncogene homolog) transcriptional start site and within the gene promoter region of Egr-1 (early growth response protein 1) specifically in the DG. Administration of the (endogenous) methyl donor S-adenosyl methionine (SAM) did not affect CpG methylation and IEG gene expression at baseline. However, administration of SAM before the FS challenge resulted in an enhanced CpG methylation at the IEG loci and suppression of IEG induction specifically in the DG and an impaired behavioral immobility response 24 h later. The stressor also specifically increased the expression of the de novo DNA methyltransferase Dnmt3a [DNA (cytosine-5-)-methyltransferase 3 alpha] in this hippocampus region. Moreover, stress resulted in an increased association of Dnmt3a enzyme with the affected CpG loci within the IEG genes. No effects of SAM were observed on stress-evoked histone modifications, including H3S10p-K14ac (histone H3, phosphorylated serine 10 and acetylated lysine-14), H3K4me3 (histone H3, trimethylated lysine-4), H3K9me3 (histone H3, trimethylated lysine-9), and H3K27me3 (histone H3, trimethylated lysine-27). We conclude that the DNA methylation status of IEGs plays a crucial role in FS-induced IEG induction in DG granule neurons and associated behavioral responses. In addition, the concentration of available methyl donor, possibly in conjunction with Dnmt3a, is critical for the responsiveness of dentate neurons to environmental stimuli in terms of gene expression and behavior.

Age-associated changes in DNA methylation across multiple tissues in an inbred mouse model.

Epigenetic disruption has been implicated in many diseases of aging, and age-associated DNA methylation changes at specific genomic loci in humans are strongly correlated with chronological age. The aim of this study was to explore the specificity of selected age-associated differentially methylated positions (aDMPs) identified in human epidemiological studies by quantifying DNA methylation across multiple tissues in homologous regions of the murine genome. We selected four high-confidence aDMPs (located in the vicinity of the ELOVL2, GLRA1, MYOD1 and PDE4C genes) and quantified DNA methylation across these regions in four tissues (blood, lung, cerebellum and hippocampus) from male and female C57BL/6J mice, ranging in age from fetal (embryonic day 17) to 630 days. We observed tissue-specific age-associated changes in DNA methylation that was directionally consistent with those observed in humans. These findings lend further support to the notion that changes in DNA methylation are associated with chronological age and suggest that these processes are often conserved across tissues and between mammalian species. Our data highlight the relevance of utilizing model systems, in which environmental and genetic influences can be carefully controlled, for the further study of these phenomena.

Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci.

We characterized DNA methylation quantitative trait loci (mQTLs) in a large collection (n = 166) of human fetal brain samples spanning 56-166 d post-conception, identifying >16,000 fetal brain mQTLs. Fetal brain mQTLs were primarily cis-acting, enriched in regulatory chromatin domains and transcription factor binding sites, and showed substantial overlap with genetic variants that were also associated with gene expression in the brain. Using tissue from three distinct regions of the adult brain (prefrontal cortex, striatum and cerebellum), we found that most fetal brain mQTLs were developmentally stable, although a subset was characterized by fetal-specific effects. Fetal brain mQTLs were enriched amongst risk loci identified in a recent large-scale genome-wide association study (GWAS) of schizophrenia, a severe psychiatric disorder with a hypothesized neurodevelopmental component. Finally, we found that mQTLs can be used to refine GWAS loci through the identification of discrete sites of variable fetal brain methylation associated with schizophrenia risk variants.

Methylomic trajectories across human fetal brain development.

Epigenetic processes play a key role in orchestrating transcriptional regulation during development. The importance of DNA methylation in fetal brain development is highlighted by the dynamic expression of de novo DNA methyltransferases during the perinatal period and neurodevelopmental deficits associated with mutations in the methyl-CpG binding protein 2 (MECP2) gene. However, our knowledge about the temporal changes to the epigenome during fetal brain development has, to date, been limited. We quantified genome-wide patterns of DNA methylation at ∼ 400,000 sites in 179 human fetal brain samples (100 male, 79 female) spanning 23 to 184 d post-conception. We identified highly significant changes in DNA methylation across fetal brain development at >7% of sites, with an enrichment of loci becoming hypomethylated with fetal age. Sites associated with developmental changes in DNA methylation during fetal brain development were significantly underrepresented in promoter regulatory regions but significantly overrepresented in regions flanking CpG islands (shores and shelves) and gene bodies. Highly significant differences in DNA methylation were observed between males and females at a number of autosomal sites, with a small number of regions showing sex-specific DNA methylation trajectories across brain development. Weighted gene comethylation network analysis (WGCNA) revealed discrete modules of comethylated loci associated with fetal age that are significantly enriched for genes involved in neurodevelopmental processes. This is, to our knowledge, the most extensive study of DNA methylation across human fetal brain development to date, confirming the prenatal period as a time of considerable epigenomic plasticity.

Methylomic profiling of human brain tissue supports a neurodevelopmental origin for schizophrenia.

BACKGROUND: Schizophrenia is a severe neuropsychiatric disorder that is hypothesized to result from disturbances ine arly brain development. There is mounting evidence to support a role for developmentally regulated epigenetic variation in the molecular etiology of the disorder. Here, we describe a systematic study of schizophrenia-associated methylomic variation in the adult brain and its relationship to changes in DNA methylation across human fetal brain development. RESULTS: We profile methylomic variation in matched prefrontal cortex and cerebellum brain tissue from schizophrenia patients and controls, identifying disease-associated differential DNA methylation at multiple loci,particularly in the prefrontal cortex, and confirming these differences in an independent set of adult brain samples.Our data reveal discrete modules of co-methylated loci associated with schizophrenia that are enriched for genes involved in neurodevelopmental processes and include loci implicated by genetic studies of the disorder. Methylomic data from human fetal cortex samples, spanning 23 to 184 days post-conception, indicates that schizophrenia-associated differentially methylated positions are significantly enriched for loci at which DNA methylation is dynamically altered during human fetal brain development. CONCLUSIONS: Our data support the hypothesis that schizophrenia has an important early neurodevelopmental component, and suggest that epigenetic mechanisms may mediate these effects.

Epigenomic and transcriptomic signatures of a Klinefelter syndrome (47,XXY) karyotype in the brain.

Klinefelter syndrome (KS) is the most common sex-chromosome aneuploidy in humans. Most affected individuals carry one extra X-chromosome (47,XXY karyotype) and the condition presents with a heterogeneous mix of reproductive, physical and psychiatric phenotypes. Although the mechanism(s) by which the supernumerary X-chromosome determines these features of KS are poorly understood, skewed X-chromosome inactivation (XCI), gene-dosage dysregulation, and the parental origin of the extra X-chromosome have all been implicated, suggesting an important role for epigenetic processes. We assessed genomic, methylomic and transcriptomic variation in matched prefrontal cortex and cerebellum samples identifying an individual with a 47,XXY karyotype who was comorbid for schizophrenia and had a notably reduced cerebellum mass compared with other individuals in the study (n = 49). We examined methylomic and transcriptomic differences in this individual relative to female and male samples with 46,XX or 46,XY karyotypes, respectively, and identified numerous locus-specific differences in DNA methylation and gene expression, with many differences being autosomal and tissue-specific. Furthermore, global DNA methylation, assessed via the interrogation of LINE-1 and Alu repetitive elements, was significantly altered in the 47,XXY patient in a tissue-specific manner with extreme hypomethylation detected in the prefrontal cortex and extreme hypermethylation in the cerebellum. This study provides the first detailed molecular characterization of the prefrontal cortex and cerebellum from an individual with a 47,XXY karyotype, identifying widespread tissue-specific epigenomic and transcriptomic alterations in the brain.

Selected rapporteur summaries from the XX World Congress of Psychiatric Genetics, Hamburg, Germany, October 14-18, 2012.

The XXth World Congress of Psychiatric Genetics (WCPG), sponsored by The International Society of Psychiatric Genetics (ISPG) took place in Hamburg, Germany on October 14-18, 2012. Approximately 600 participants gathered to discuss the latest findings in this rapidly advancing field. The following report was written by student travel awardees. Each was assigned sessions as rapporteurs. This manuscript represents topics covered in most, but not all, oral presentations during the conference, and some of the major notable new findings reported at this 2012 WCPG.