Sean M. Buchanan

Bio: Sean M. Buchanan is an academic researcher from Harvard University. The author has contributed to research in topics: GDF11 & Genome-wide association study. The author has an hindex of 11, co-authored 16 publications receiving 731 citations. Previous affiliations of Sean M. Buchanan include University of Pittsburgh & Brigham and Women's Hospital.

Single-cell transcriptomic profiling of the aging mouse brain.

Abstract: The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain ) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.

Behavioral idiosyncrasy reveals genetic control of phenotypic variability

Abstract: Quantitative genetics has primarily focused on describing genetic effects on trait means and largely ignored the effect of alternative alleles on trait variability, potentially missing an important axis of genetic variation contributing to phenotypic differences among individuals. To study the genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used Drosophila inbred lines and measured the spontaneous locomotor behavior of flies walking individually in Y-shaped mazes, focusing on variability in locomotor handedness, an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals, whereas lines with low variability behaved as although they tossed a coin at each left/right turn decision. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a, implicates a neuropil in the central complex of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination. We validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. Our study reveals the constellation of phenotypes that can arise from a single genotype and shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variabililty. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.

Biochemistry and Biology of GDF11 and Myostatin: Similarities, Differences, and Questions for Future Investigation.

Abstract: Growth differentiation factor 11 (GDF11) and myostatin (or GDF8) are closely related members of the transforming growth factor β superfamily and are often perceived to serve similar or overlapping roles. Yet, despite commonalities in protein sequence, receptor utilization and signaling, accumulating evidence suggests that these 2 ligands can have distinct functions in many situations. GDF11 is essential for mammalian development and has been suggested to regulate aging of multiple tissues, whereas myostatin is a well-described negative regulator of postnatal skeletal and cardiac muscle mass and modulates metabolic processes. In this review, we discuss the biochemical regulation of GDF11 and myostatin and their functions in the heart, skeletal muscle, and brain. We also highlight recent clinical findings with respect to a potential role for GDF11 and/or myostatin in humans with heart disease. Finally, we address key outstanding questions related to GDF11 and myostatin dynamics and signaling during development, growth, and aging.

Neuronal control of locomotor handedness in Drosophila

Abstract: Genetically identical individuals display variability in their physiology, morphology, and behaviors, even when reared in essentially identical environments, but there is little mechanistic understanding of the basis of such variation. Here, we investigated whether Drosophila melanogaster displays individual-to-individual variation in locomotor behaviors. We developed a new high-throughout platform capable of measuring the exploratory behavior of hundreds of individual flies simultaneously. With this approach, we find that, during exploratory walking, individual flies exhibit significant bias in their left vs. right locomotor choices, with some flies being strongly left biased or right biased. This idiosyncrasy was present in all genotypes examined, including wild-derived populations and inbred isogenic laboratory strains. The biases of individual flies persist for their lifetime and are nonheritable: i.e., mating two left-biased individuals does not yield left-biased progeny. This locomotor handedness is uncorrelated with other asymmetries, such as the handedness of gut twisting, leg-length asymmetry, and wing-folding preference. Using transgenics and mutants, we find that the magnitude of locomotor handedness is under the control of columnar neurons within the central complex, a brain region implicated in motor planning and execution. When these neurons are silenced, exploratory laterality increases, with more extreme leftiness and rightiness. This observation intriguingly implies that the brain may be able to dynamically regulate behavioral individuality.

Growth Differentiation Factor 11 treatment leads to neuronal and vascular improvements in the hippocampus of aged mice

Abstract: Aging is the biggest risk factor for several neurodegenerative diseases. Parabiosis experiments have established that old mouse brains are improved by exposure to young mouse blood. Previously, our lab showed that delivery of Growth Differentiation Factor 11 (GDF11) to the bloodstream increases the number of neural stem cells and positively affects vasculature in the subventricular zone of old mice. Our new study demonstrates that GDF11 enhances hippocampal neurogenesis, improves vasculature and increases markers of neuronal activity and plasticity in the hippocampus and cortex of old mice. Our experiments also demonstrate that systemically delivered GDF11, rather than crossing the blood brain barrier, exerts at least some of its effects by acting on brain endothelial cells. Thus, by targeting the cerebral vasculature, GDF11 has a very different mechanism from that of previously studied circulating factors acting to improve central nervous system (CNS) function without entering the CNS.

Ageing, neurodegeneration and brain rejuvenation

Abstract: Although systemic diseases take the biggest toll on human health and well-being, increasingly, a failing brain is the arbiter of a death preceded by a gradual loss of the essence of being. Ageing, which is fundamental to neurodegeneration and dementia, affects every organ in the body and seems to be encoded partly in a blood-based signature. Indeed, factors in the circulation have been shown to modulate ageing and to rejuvenate numerous organs, including the brain. The discovery of such factors, the identification of their origins and a deeper understanding of their functions is ushering in a new era in ageing and dementia research.

Structure-based prediction of protein–protein interactions on a genome-wide scale

Abstract: Protein–protein interactions, essential for understanding how a cell functions, are predicted using a new method that combines protein structure with other computationally and experimentally derived clues The analysis of protein-interaction networks is essential to an understanding of the regulatory processes in a living cell Many methods have been developed with a view to predicting protein–protein interactions (PPIs) at a genome-wide level, although the differences obtained using these approaches suggest that there are still factors unaccounted for Barry Honig and colleagues have developed a new way of predicting PPIs that is based on the proteins' three-dimensional structures and functional data Tests of several predictions of the new algorithm, known as PREPPI, confirm the accuracy of the results The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms1,2 Much of our present knowledge derives from high-throughput techniques such as the yeast two-hybrid assay and affinity purification3, as well as from manual curation of experiments on individual systems4 A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein–protein interactions (PPIs)5,6 Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages7,8,9 Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins

Molecular mechanisms of proteasome assembly

Abstract: The 26S proteasome is a highly conserved protein degradation machine that consists of the 20S proteasome and 19S regulatory particles, which include 14 and 19 different polypeptides, respectively. How the proteasome components are assembled is a fundamental question towards understanding the process of protein degradation and its functions in diverse biological processes. Several proteasome-dedicated chaperones are involved in the efficient and correct assembly of the 20S proteasome. These chaperones help the initiation and progression of the assembly process by transiently associating with proteasome precursors. By contrast, little is known about the assembly of the 19S regulatory particles, but several hints have emerged.

Deciphering cell-cell interactions and communication from gene expression.

Abstract: Cell-cell interactions orchestrate organismal development, homeostasis and single-cell functions. When cells do not properly interact or improperly decode molecular messages, disease ensues. Thus, the identification and quantification of intercellular signalling pathways has become a common analysis performed across diverse disciplines. The expansion of protein-protein interaction databases and recent advances in RNA sequencing technologies have enabled routine analyses of intercellular signalling from gene expression measurements of bulk and single-cell data sets. In particular, ligand-receptor pairs can be used to infer intercellular communication from the coordinated expression of their cognate genes. In this Review, we highlight discoveries enabled by analyses of cell-cell interactions from transcriptomic data and review the methods and tools used in this context.