Spectral Sequence Motif Discovery

Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, motif finding algorithms of increasingly high performance are required to process the big datasets produced by new high-throughput sequencing technologies. Most existing algorithms are computationally demanding and often cannot support the large size of new experimental data. We present a new motif discovery algorithm that is built on a recent machine learning technique, referred to as Method of Moments. Based on spectral decompositions, this method is robust under model misspecification and is not prone to locally optimal solutions. We obtain an algorithm that is extremely fast and designed for the analysis of big sequencing data. In a few minutes, we can process datasets of hundreds of thousand sequences and extract motif profiles that match those computed by various state-of-the-art algorithms.Comment: 20 pages, 3 figures, 1 tabl

Motif affinity and mass spectrometry proteomic approach for the discovery of cellular AMPK targets: identification of mitochondrial fission factor as a new AMPK substrate

AMP-activated protein kinase (AMPK) is a key cellular energy sensor and regulator of metabolic homeostasis. Although it is best known for its effects on carbohydrate and lipid metabolism, AMPK is implicated in diverse cellular processes, including mitochondrial biogenesis, autophagy, and cell growth and proliferation. To further our understanding of energy homeostasis through AMPK-dependent processes, the design and application of approaches to identify and characterise novel AMPK substrates are invaluable. Here, we report an affinity proteomicstrategy for the discovery and validation of AMPK targets using an antibody to isolate proteins containing the phospho-AMPK substrate recognition motif from hepatocytes that had been treated with pharmacological AMPK activators. We identified 57 proteins that were uniquely enriched in the activator-treated hepatocytes, but were absent in hepatocytes lacking AMPK. We focused on two candidates, cingulin and mitochondrial fission factor (MFF), and further characterised/validated them as AMPK-dependent targets by immunoblotting with phosphorylation site-specific antibodies. A small-molecule AMPK activator caused transient phosphorylation of endogenous cingulin at S137 in intestinal Caco2 cells. Multiple splice-variants of MFF appear to express in hepatocytes and we identified a common AMPK-dependent phospho-site (S129) in all the 3 predominant variants spanning the mass range and a short variant-specific site (S146). Collectively, our proteomic-based approach using a phospho-AMPK substrate antibody in combination with genetic models and selective AMPK activators will provide a powerful and reliable platform for identifying novel AMPK-dependent cellular targets

ClgR regulation of chaperone and protease systems is essential for Mycobacterium tuberculosis parasitism of the macrophage

Chaperone and protease systems play essential roles in cellular homeostasis and have vital functions in controlling the abundance of specific cellular proteins involved in processes such as transcription, replication, metabolism and virulence. Bacteria have evolved accurate regulatory systems to control the expression and function of chaperones and potentially destructive proteases. Here, we have used a combination of transcriptomics, proteomics and targeted mutagenesis to reveal that the clp gene regulator (ClgR) of Mycobacterium tuberculosis activates the transcription of at least ten genes, including four that encode protease systems (ClpP1/C, ClpP2/C, PtrB and HtrA-like protease Rv1043c) and three that encode chaperones (Acr2, ClpB and the chaperonin Rv3269). Thus, M. tuberculosis ClgR controls a larger network of protein homeostatic and regulatory systems than ClgR in any other bacterium studied to date. We demonstrate that ClgR-regulated transcriptional activation of these systems is essential for M. tuberculosis to replicate in macrophages. Furthermore, we observe that this defect is manifest early in infection, as M. tuberculosis lacking ClgR is deficient in the ability to control phagosome pH 1 h post-phagocytosis

Network Density of States

Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of associated differential operators. But the translation from spectral geometry to spectral graph theory has largely focused on results involving only a few extreme eigenvalues and their associated eigenvalues. Unlike in geometry, the study of graphs through the overall distribution of eigenvalues - the spectral density - is largely limited to simple random graph models. The interior of the spectrum of real-world graphs remains largely unexplored, difficult to compute and to interpret. In this paper, we delve into the heart of spectral densities of real-world graphs. We borrow tools developed in condensed matter physics, and add novel adaptations to handle the spectral signatures of common graph motifs. The resulting methods are highly efficient, as we illustrate by computing spectral densities for graphs with over a billion edges on a single compute node. Beyond providing visually compelling fingerprints of graphs, we show how the estimation of spectral densities facilitates the computation of many common centrality measures, and use spectral densities to estimate meaningful information about graph structure that cannot be inferred from the extremal eigenpairs alone.Comment: 10 pages, 7 figure

Competing protein-protein interactions regulate binding of Hsp27 to its client protein tau.

Small heat shock proteins (sHSPs) are a class of oligomeric molecular chaperones that limit protein aggregation. However, it is often not clear where sHSPs bind on their client proteins or how these protein-protein interactions (PPIs) are regulated. Here, we map the PPIs between human Hsp27 and the microtubule-associated protein tau (MAPT/tau). We find that Hsp27 selectively recognizes two aggregation-prone regions of tau, using the conserved β4-β8 cleft of its alpha-crystallin domain. The β4-β8 region is also the site of Hsp27-Hsp27 interactions, suggesting that competitive PPIs may be an important regulatory paradigm. Indeed, we find that each of the individual PPIs are relatively weak and that competition for shared sites seems to control both client binding and Hsp27 oligomerization. These findings highlight the importance of multiple, competitive PPIs in the function of Hsp27 and suggest that the β4-β8 groove acts as a tunable sensor for clients

Expanding the set of rhodococcal Baeyer–Villiger monooxygenases by high-throughput cloning, expression and substrate screening

To expand the available set of Baeyer–Villiger monooxygenases (BVMOs), we have created expression constructs for producing 22 Type I BVMOs that are present in the genome of Rhodococcus jostii RHA1. Each BVMO has been probed with a large panel of potential substrates. Except for testing their substrate acceptance, also the enantioselectivity of some selected BVMOs was studied. The results provide insight into the biocatalytic potential of this collection of BVMOs and expand the biocatalytic repertoire known for BVMOs. This study also sheds light on the catalytic capacity of this large set of BVMOs that is present in this specific actinomycete. Furthermore, a comparative sequence analysis revealed a new BVMO-typifying sequence motif. This motif represents a useful tool for effective future genome mining efforts.