A new R package and web application for detecting bilateral asymmetry in parasitic infections.

When parasites invade paired structures of their host non-randomly, the resulting asymmetry may have both pathological and ecological significance. To facilitate the detection and visualisation of asymmetric infections we have developed a free software tool, Analysis of Symmetry of Parasitic Infections (ASPI). This tool has been implemented as an R package (https://cran.r-project.org/package=aspi) and a web application (https://wayland.shinyapps.io/aspi). ASPI can detect both consistent bias towards one side, and inconsistent bias in which the left side is favoured in some hosts and the right in others. Application of ASPI is demonstrated using previously unpublished data on the distribution of metacercariae of species of Diplostomum von Nordmann, 1832 in the eyes of ruffe Gymnocephalus cernua (Linnaeus). Invasion of the lenses appeared to be random, with the proportion of metacercariae in the left and right lenses showing the pattern expected by chance. However, analysis of counts of metacercariae from the humors, choroid and retina revealed asymmetry between eyes in 38% of host fish

Behavioural analysis of single-cell aneural ciliate, Stentor roeseli, using machine learning approaches.

There is still a significant gap between our understanding of neural circuits and the behaviours they compute-i.e. the computations performed by these neural networks (Carandini 2012 Nat. Neurosci.15, 507-509. (doi:10.1038/nn.3043)). Cellular decision-making processes, learning, behaviour and memory formation-all that have been only associated with animals with neural systems-have also been observed in many unicellular aneural organisms, namely Physarum, Paramecium and Stentor (Tang & Marshall2018 Curr. Biol.28, R1180-R1184. (doi:10.1016/j.cub.2018.09.015)). As these are fully functioning organisms, yet being unicellular, there is a much better chance to elucidate the detailed mechanisms underlying these learning processes in these organisms without the complications of highly interconnected neural circuits. An intriguing learning behaviour observed in Stentor roeseli (Jennings 1902 Am. J. Physiol. Legacy Content8, 23-60. (doi:10.1152/ajplegacy.1902.8.1.23)) when stimulated with carmine has left scientists puzzled for more than a century. So far, none of the existing learning paradigm can fully encapsulate this particular series of five characteristic avoidance reactions. Although we were able to observe all responses described in the literature and in a previous study (Dexter et al. 2019), they do not conform to any particular learning model. We then investigated whether models inferred from machine learning approaches, including decision tree, random forest and feed-forward artificial neural networks could infer and predict the behaviour of S. roeseli. Our results showed that an artificial neural network with multiple 'computational' neurons is inefficient at modelling the single-celled ciliate's avoidance reactions. This has highlighted the complexity of behaviours in aneural organisms. Additionally, this report will also discuss the significance of elucidating molecular details underlying learning and decision-making processes in these unicellular organisms, which could offer valuable insights that are applicable to higher animals.KMT is funded by Cambridge Trust Scholarship and Trinity Overseas Bursaries; SP is funded by the Cambridge-DBT lectureship

Gene expression profiling of mammary gland development reveals putative roles for death receptors and immune mediators in post-lactational regression

INTRODUCTION: In order to gain a better understanding of the molecular processes that underlie apoptosis and tissue regression in mammary gland, we undertook a large-scale analysis of transcriptional changes during the mouse mammary pregnancy cycle, with emphasis on the transition from lactation to involution. METHOD: Affymetrix microarrays, representing 8618 genes, were used to compare mammary tissue from 12 time points (one virgin, three gestation, three lactation and five involution stages). Six animals were used for each time point. Common patterns of gene expression across all time points were identified and related to biological function. RESULTS: The majority of significantly induced genes in involution were also differentially regulated at earlier stages in the pregnancy cycle. This included a marked increase in inflammatory mediators during involution and at parturition, which correlated with leukaemia inhibitory factor–Stat3 (signal transducer and activator of signalling-3) signalling. Before involution, expected increases in cell proliferation, biosynthesis and metabolism-related genes were observed. During involution, the first 24 hours after weaning was characterized by a transient increase in expression of components of the death receptor pathways of apoptosis, inflammatory cytokines and acute phase response genes. After 24 hours, regulators of intrinsic apoptosis were induced in conjunction with markers of phagocyte activity, matrix proteases, suppressors of neutrophils and soluble components of specific and innate immunity. CONCLUSION: We provide a resource of mouse mammary gene expression data for download or online analysis. Here we highlight the sequential induction of distinct apoptosis pathways in involution and the stimulation of immunomodulatory signals, which probably suppress the potentially damaging effects of a cellular inflammatory response while maintaining an appropriate antimicrobial and phagocytic environment

Fast imaging of live organisms with sculpted light sheets.

Light-sheet microscopy is an increasingly popular technique in the life sciences due to its fast 3D imaging capability of fluorescent samples with low photo toxicity compared to confocal methods. In this work we present a new, fast, flexible and simple to implement method to optimize the illumination light-sheet to the requirement at hand. A telescope composed of two electrically tuneable lenses enables us to define thickness and position of the light-sheet independently but accurately within milliseconds, and therefore optimize image quality of the features of interest interactively. We demonstrated the practical benefit of this technique by 1) assembling large field of views from tiled single exposure each with individually optimized illumination settings; 2) sculpting the light-sheet to trace complex sample shapes within single exposures. This technique proved compatible with confocal line scanning detection, further improving image contrast and resolution. Finally, we determined the effect of light-sheet optimization in the context of scattering tissue, devising procedures for balancing image quality, field of view and acquisition speed.This work was funded by grants from the Wellcome Trust, the Medical Research Council, the CamBridgeSense network, Carlsberg Foundation, the Alzheimer Research UK Trust and the Biotechnology and Biological Sciences Research Council and the Wolfson Foundation.This is the final version of the article. It first appeared at http://dx.doi.org/10.1038/srep09385

Metabolic changes in schizophrenia and human brain evolution.

BACKGROUND: Despite decades of research, the molecular changes responsible for the evolution of human cognitive abilities remain unknown. Comparative evolutionary studies provide detailed information about DNA sequence and mRNA expression differences between humans and other primates but, in the absence of other information, it has proved very difficult to identify molecular pathways relevant to human cognition. RESULTS: Here, we compare changes in gene expression and metabolite concentrations in the human brain and compare them to the changes seen in a disorder known to affect human cognitive abilities, schizophrenia. We find that both genes and metabolites relating to energy metabolism and energy-expensive brain functions are altered in schizophrenia and, at the same time, appear to have changed rapidly during recent human evolution, probably as a result of positive selection. CONCLUSION: Our findings, along with several previous studies, suggest that the evolution of human cognitive abilities was accompanied by adaptive changes in brain metabolism, potentially pushing the human brain to the limit of its metabolic capabilities.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evolutionary divergence of novel open reading frames in cichlids speciation

Funder: DBT-Cambridge LectureshipFunder: Wellcome Trust Senior Investigator AwardAbstract: Novel open reading frames (nORFs) with coding potential may arise from noncoding DNA. Not much is known about their emergence, functional role, fixation in a population or contribution to adaptive radiation. Cichlids fishes exhibit extensive phenotypic diversification and speciation. Encounters with new environments alone are not sufficient to explain this striking diversity of cichlid radiation because other taxa coexistent with the Cichlidae demonstrate lower species richness. Wagner et al. analyzed cichlid diversification in 46 African lakes and reported that both extrinsic environmental factors and intrinsic lineage-specific traits related to sexual selection have strongly influenced the cichlid radiation, which indicates the existence of unknown molecular mechanisms responsible for rapid phenotypic diversification, such as emergence of novel open reading frames (nORFs). In this study, we integrated transcriptomic and proteomic signatures from two tissues of two cichlids species, identified nORFs and performed evolutionary analysis on these nORF regions. Our results suggest that the time scale of speciation of the two species and evolutionary divergence of these nORF genomic regions are similar and indicate a potential role for these nORFs in speciation of the cichlid fishes

Author Correction: Evolutionary divergence of novel open reading frames in cichlids speciation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.</jats:p

Evolutionary divergence of novel open reading frames in cichlids speciation

Funder: DBT-Cambridge LectureshipFunder: Wellcome Trust Senior Investigator AwardAbstract: Novel open reading frames (nORFs) with coding potential may arise from noncoding DNA. Not much is known about their emergence, functional role, fixation in a population or contribution to adaptive radiation. Cichlids fishes exhibit extensive phenotypic diversification and speciation. Encounters with new environments alone are not sufficient to explain this striking diversity of cichlid radiation because other taxa coexistent with the Cichlidae demonstrate lower species richness. Wagner et al. analyzed cichlid diversification in 46 African lakes and reported that both extrinsic environmental factors and intrinsic lineage-specific traits related to sexual selection have strongly influenced the cichlid radiation, which indicates the existence of unknown molecular mechanisms responsible for rapid phenotypic diversification, such as emergence of novel open reading frames (nORFs). In this study, we integrated transcriptomic and proteomic signatures from two tissues of two cichlids species, identified nORFs and performed evolutionary analysis on these nORF regions. Our results suggest that the time scale of speciation of the two species and evolutionary divergence of these nORF genomic regions are similar and indicate a potential role for these nORFs in speciation of the cichlid fishes

Evolution of Neuronal and Endothelial Transcriptomes in Primates

The study of gene expression evolution in vertebrates has hitherto focused on the analysis of transcriptomes in tissues of different species. However, because a tissue is made up of different cell types, and cell types differ with respect to their transcriptomes, the analysis of tissues offers a composite picture of transcriptome evolution. The isolation of individual cells from tissue sections opens up the opportunity to study gene expression evolution at the cell type level. We have stained neurons and endothelial cells in human brains by antibodies against cell type-specific marker proteins, isolated the cells using laser capture microdissection, and identified genes preferentially expressed in the two cell types. We analyze these two classes of genes with respect to their expression in 62 different human tissues, with respect to their expression in 44 human “postmortem” brains from different developmental stages and with respect to between-species brain expression differences. We find that genes preferentially expressed in neurons differ less across tissues and developmental stages than genes preferentially expressed in endothelial cells. We also observe less expression differences within primate species for neuronal transcriptomes. In stark contrast, we see more gene expression differences between humans, chimpanzees, and rhesus macaques relative to within-species differences in genes expressed preferentially in neurons than in genes expressed in endothelial cells. This suggests that neuronal and endothelial transcriptomes evolve at different rates within brain tissue

Pan-cancer analysis of transcripts encoding novel open-reading frames (nORFs) and their potential biological functions.

Uncharacterized and unannotated open-reading frames, which we refer to as novel open reading frames (nORFs), may sometimes encode peptides that remain unexplored for novel therapeutic opportunities. To our knowledge, no systematic identification and characterization of transcripts encoding nORFs or their translation products in cancer, or in any other physiological process has been performed. We use our curated nORFs database (nORFs.org), together with RNA-Seq data from The Cancer Genome Atlas (TCGA) and Genotype-Expression (GTEx) consortiums, to identify transcripts containing nORFs that are expressed frequently in cancer or matched normal tissue across 22 cancer types. We show nORFs are subject to extensive dysregulation at the transcript level in cancer tissue and that a small subset of nORFs are associated with overall patient survival, suggesting that nORFs may have prognostic value. We also show that nORF products can form protein-like structures with post-translational modifications. Finally, we perform in silico screening for inhibitors against nORF-encoded proteins that are disrupted in stomach and esophageal cancer, showing that they can potentially be targeted by inhibitors. We hope this work will guide and motivate future studies that perform in-depth characterization of nORF functions in cancer and other diseases