Performing group-level functional image analyses based on homologous functional regions mapped in individuals.
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ABSTRACT:
SUBMITTER: Li M
PROVIDER: S-EPMC6448916 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The first 1000 days from conception to two-years of age are a critical period in brain development, and there is an increasing drive for developing technologies to help advance our understanding of neurodevelopmental processes during this time. Functional near-infrared spectroscopy (fNIRS) has enabled longitudinal infant brain function to be studied in a multitude of settings. Conventional fNIRS analyses tend to occur in the channel-space, where data from equivalent channels across individuals are combined, which implicitly assumes that head size and source-detector positions (i.e. array position) on the scalp are constant across individuals. The validity of such assumptions in longitudinal infant fNIRS analyses, where head growth is most rapid, has not previously been investigated. We employed an image reconstruction approach to analyse fNIRS data collected from a longitudinal cohort of infants in The Gambia aged 5- to 12-months. This enabled us to investigate the effect of variability in both head size and array position on the anatomical and statistical inferences drawn from the data at both the group- and the individual-level. We also sought to investigate the impact of group size on inferences drawn from the data. We found that variability in array position was the driving factor between differing inferences drawn from the data at both the individual- and group-level, but its effect was weakened as group size increased towards the full cohort size (N = 53 at 5-months, N = 40 at 8-months and N = 45 at 12-months). We conclude that, at the group sizes in our dataset, group-level channel-space analysis of longitudinal infant fNIRS data is robust to assumptions about head size and array position given the variability in these parameters in our dataset. These findings support a more widespread use of image reconstruction techniques in longitudinal infant fNIRS studies.
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Project description:We have identified the cyclin domain-containing proteins encoded by the genomes of 17 species of Aspergillus as well as 15 members of other genera of filamentous ascomycetes. Phylogenetic analyses reveal that the cyclins fall into three groups, as in other eukaryotic phyla, and, more significantly, that they are remarkably conserved in these fungi. All 32 species examined, for example, have three group I cyclins, cyclins that are particularly important because they regulate the cell cycle, and these are highly conserved. Within the group I cyclins there are three distinct clades, and each fungus has a single member of each clade. These findings are in marked contrast to the yeasts Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Candida albicans, which have more numerous group I cyclins. These results indicate that findings on cyclin function made with a model Aspergillus species, such as A. nidulans, are likely to apply to other Aspergilli and be informative for a broad range of filamentous ascomycetes. In this regard, we note that the functions of only one Aspergillus group I cyclin have been analysed (NimECyclin B of A. nidulans). We have consequently carried out an analysis of the members of the other two clades using A. nidulans as our model. We have found that one of these cyclins, PucA, is essential, but deletion of PucA in a strain carrying a deletion of CdhA, an activator of the anaphase promoting complex/cyclosome (APC/C), is not lethal. These data, coupled with data from heterokaryon rescue experiments, indicate that PucA is an essential G1/S cyclin that is required for the inactivation of the APC/C-CdhA, which, in turn, allows the initiation of the S phase of the cell cycle. Our data also reveal that PucA has additional, non-essential, roles in the cell cycle in interphase. The A. nidulans member of the third clade (AN2137) has not previously been named or analyzed. We designate this gene clbA. ClbA localizes to kinetochores from mid G2 until just prior to chromosomal condensation. Deletion of clbA does not affect viability. However, by using a regulatable promoter system new to Aspergillus, we have found that expression of a version of ClbA in which the destruction box sequences have been removed is lethal and causes a mitotic arrest and a high frequency of non-disjunction. Thus, although ClbA is not essential, its timely destruction is essential for viability, chromosomal disjunction, and successful completion of mitosis.
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Project description:Many recent developments surrounding the functional network organization of the human brain have focused on data that have been averaged across groups of individuals. While such group-level approaches have shed considerable light on the brain's large-scale distributed systems, they conceal individual differences in network organization, which recent work has demonstrated to be common and widespread. This individual variability produces noise in group analyses, which may average together regions that are part of different functional systems across participants, limiting interpretability. However, cost and feasibility constraints may limit the possibility for individual-level mapping within studies. Here our goal was to leverage information about individual-level brain organization to probabilistically map common functional systems and identify locations of high inter-subject consensus for use in group analyses. We probabilistically mapped 14 functional networks in multiple datasets with relatively high amounts of data. All networks show "core" (high-probability) regions, but differ from one another in the extent of their higher-variability components. These patterns replicate well across four datasets with different participants and scanning parameters. We produced a set of high-probability regions of interest (ROIs) from these probabilistic maps; these and the probabilistic maps are made publicly available, together with a tool for querying the network membership probabilities associated with any given cortical location. These quantitative estimates and public tools may allow researchers to apply information about inter-subject consensus to their own fMRI studies, improving inferences about systems and their functional specializations.
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Project description:Tryptic proteolysis of the small GTPases Rab4 and Rab5 is a multi-step, nucleotide-dependent process. Using N-terminal peptide sequencing, matrix-assisted laser desorption ionization-time-of-flight MS and molecular modelling, we identified the three initial sites of proteolysis in Rab5 as Arg-4, Arg-81 and Arg-197. Arg-4 and Arg-81 lie within regions previously implicated in Rab5 endocytic function, and Arg-197 lies in a region involved in membrane targeting. Topologically, Arg-81 lies within the conformationally variable Switch II region shown to be important for protein-protein interactions of other GTPases. Homology modelling studies on Rab5 indicate that the Arg-81 side chain is buried in the Rab5 GTP conformation, but is solvent-accessible in the GDP conformation, explaining the dependence of proteolysis on nucleotides. Peptide mapping of Rab4 was performed to take advantage of additional scissile bonds within Switch II to determine more precisely the limits of the nucleotide-dependent protease-accessible region. The Rab4 cleavage sites corresponded to Arg-81 and Pro-87 of Rab5, and taken together with the finding that Rab5 was not cleaved at Arg-91 this analysis defines an eight-residue surface-exposed conformationally variable region lying in the centre of Switch II. A sequence comparison of Rab proteins shows these eight residues to have a loosely conserved motif that we term Switch II(v) for its relative variability. C-terminal to Switch II(v) is a highly conserved Rab-specific YYRGA motif that we term Switch II(c) for its constant sequence. N-terminal to Switch II(v) is a sequence-invariant G-domain involved in nucleotide binding and hydrolysis. We propose that the Rab Switch II(v) region imparts specificity to nucleotide-dependent protein-protein interactions.
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Project description:Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601-0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to 'black-box' methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.
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Project description:The explosion of protein sequences deduced from genetic code has led to both a problem and a potential resource: Efficient data use requires interpreting the functional impact of sequence change without experimentally characterizing each protein variant. Several groups have hypothesized that interpretation could be aided by analyzing the sequences of naturally occurring homologues. To that end, myriad sequence/function analyses have been developed to predict which conserved, semi-conserved, and nonconserved positions are functionally important. These positions must be discriminated from the nonconserved positions that are functionally silent. However, the assumptions that underlie sequence analyses are based on experimental results that are sparse and usually designed to address different questions. Here, we use three homologues from a test family common to bioinformatics-the LacI/GalR transcription repressors-to test a common assumption: If a position is functionally important for one family member, it has similar importance in all homologues. We generated experimental sequence/function information for each nonconserved position in the 18 amino acids that link the DNA-binding and regulatory domains of three LacI/GalR homologues. We find that the functional importance of each position is preserved among the three linkers, albeit to different degrees. We also find that every linker position contributes to function, which has twofold implications. (1) Since the linker positions range from highly conserved to semi-conserved to nonconserved and contribute to affinity, selectivity, and allosteric response, we assert that sequence/function analyses must identify positions in the LacI/GalR linkers to be qualified as "successful". Many analyses overlook this region since most of the residues do not directly contact ligand. (2) No position in the LacI/GalR linker is functionally silent. This finding is inconsistent with another underlying principle of many analyses: Using sequence sets to discriminate important from non-contributing positions obligates silent positions, which denotes that most homologues tolerate a variety of amino acid substitutions at the position without functional change. Instead, additional combinatorial mutants in the LacI/GalR linkers show that particular substitutions can be silent in a context-dependent manner. Thus, specific permutations of sequence change (rather than change at silent positions) would facilitate neutral drift during evolution. Finally, the combinatorial mutants also reveal functional synergy between semi- and nonconserved positions. Such functional relationships would be missed by analyses that rely primarily upon co-evolution.
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