Peter Krusche

Phase locking and multiple oscillating attractors for the coupled mammalian clock and cell cycle

Significance In tissues such as bone marrow, intestinal mucosa, or regenerating liver, the daily rhythm of cell division is controlled by the cell’s circadian clock. Determining how this clock organizes important processes such as cell division, apoptosis, and DNA damage repair is key to understanding the links between circadian dysfunction and malignant cell proliferation. We show that in proliferating mouse fibroblasts there is more than one way in which the clock and cell cycle synchronize their oscillations and that one of them is the biological equivalent of the phase locking first discovered by Huygens in the 17th century when he coupled two clocks together. When phase-locked two coupled oscillators have a fixed relative phase and oscillate with a common frequency. Daily synchronous rhythms of cell division at the tissue or organism level are observed in many species and suggest that the circadian clock and cell cycle oscillators are coupled. For mammals, despite known mechanistic interactions, the effect of such coupling on clock and cell cycle progression, and hence its biological relevance, is not understood. In particular, we do not know how the temporal organization of cell division at the single-cell level produces this daily rhythm at the tissue level. Here we use multispectral imaging of single live cells, computational methods, and mathematical modeling to address this question in proliferating mouse fibroblasts. We show that in unsynchronized cells the cell cycle and circadian clock robustly phase lock each other in a 1:1 fashion so that in an expanding cell population the two oscillators oscillate in a synchronized way with a common frequency. Dexamethasone-induced synchronization reveals additional clock states. As well as the low-period phase-locked state there are distinct coexisting states with a significantly higher period clock. Cells transition to these states after dexamethasone synchronization. The temporal coordination of cell division by phase locking to the clock at a single-cell level has significant implications because disordered circadian function is increasingly being linked to the pathogenesis of many diseases, including cancer.

Conserved Noncoding Sequences Highlight Shared Components of Regulatory Networks in Dicotyledonous Plants

This study identifies regions of noncoding DNA in dicot plants that are likely to facilitate complex regulation of genes by binding multiple transcription factors. Regulatory mechanisms that the model organism Arabidopsis is likely to share with crop plants provide a focus for research that has real-world applications. Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research.

Cyclin-dependent kinase inhibitor p20 controls circadian cell-cycle timing

Specific stages of the cell cycle are often restricted to particular times of day because of regulation by the circadian clock. In zebrafish, both mitosis (M phase) and DNA synthesis (S phase) are clock-controlled in cell lines and during embryo development. Despite the ubiquitousness of this phenomenon, relatively little is known about the underlying mechanism linking the clock to the cell cycle. In this study, we describe an evolutionarily conserved cell-cycle regulator, cyclin-dependent kinase inhibitor 1d (20 kDa protein, p20), which along with p21, is a strongly rhythmic gene and directly clock-controlled. Both p20 and p21 regulate the G1/S transition of the cell cycle. However, their expression patterns differ, with p20 predominant in developing brain and peak expression occurring 6 h earlier than p21. p20 expression is also p53-independent in contrast to p21 regulation. Such differences provide a unique mechanism whereby S phase is set to different times of day in a tissue-specific manner, depending on the balance of these two inhibitors.

Evolutionary analysis of regulatory sequences (EARS) in plants

Identification of regulatory sequences within non-coding regions of DNA is an essential step towards elucidation of gene networks. This approach constitutes a major challenge, however, as only a very small fraction of non-coding DNA is thought to contribute to gene regulation. The mapping of regulatory regions traditionally involves the laborious construction of promoter deletion series which are then fused to reporter genes and assayed in transgenic organisms. Bioinformatic methods can be used to scan sequences for matches for known regulatory motifs, however these methods are currently hampered by the relatively small amount of such motifs and by a high false-discovery rate. Here, we demonstrate a robust and highly sensitive, in silico method to identify evolutionarily conserved regions within non-coding DNA. Sequence conservation within these regions is taken as evidence for evolutionary pressure against mutations, which is suggestive of functional importance. We test this method on a small set of well characterised promoters, and show that it successfully identifies known regulatory regions. We further show that these evolutionarily conserved sequences contain clusters of transcription binding sites, often described as regulatory modules. A version of the tool optimised for the analysis of plant promoters is available online at http://wsbc.warwick.ac.uk/ears/main.php.

New algorithms for efficient parallel string comparison

In this paper, we show new parallel algorithms for a set of classical string comparison problems: computation of string alignments, longest common subsequences (LCS) or edit distances, and longest increasing subsequence computation. These problems have a wide range of applications, in particular in computational biology and signal processing. We discuss the scalability of our new parallel algorithms in computation time, in memory, and in communication. Our new algorithms are based on an efficient parallel method for (min,+)-multiplication of distance matrices. The core result of this paper is a scalable parallel algorithm for multiplying implicit simple unit-Monge matrices of size <i>n</i> x <i>n</i> on <i>p</i> processors using time <i>O</i>( <i>n</i> log <i>n</i> ‾ <i>p</i>). communication <i>O</i>(<i>n</i> log <i>p</i>) ‾ <i>p</i>) and <i>O</i>(log <i>p</i>) supersteps. This algorithm allows us to implement scalable LCS computation for two strings of length <i>n</i> using time <i>O</i>(<i>n</i>² ‾ <i>p</i>) and communication <i>O</i>(<i>n</i> ‾ √ <i>p</i>), requiring local memory of size <i>O</i>(<i>n</i> ‾ √ <i>p</i>) on each processor. Furthermore, our algorithm can be used to obtain the first generally work-scalable algorithm for computing the longest increasing subsequence (LIS). Our algorithm for LIS computation requires computation <i>O</i>(<i>n</i> log² <i>n</i> ‾ <i>p</i>), communication <i>O</i>(<i>n</i> log <i>p</i>)/ <i>p</i>), and <i>O</i>(log² <i>p</i>) supersteps for computing the LIS of a sequence of length <i>n</i>. This is within a log n factor of work-optimality for the LIS problem, which can be solved sequentially in time O(<i>n</i> log <i>n</i>) in the comparison-based model. Our LIS algorithm is also within a log <i>p</i>-factor of achieving perfectly scalable communication and furthermore has perfectly scalable memory size requirements of <i>O</i>(<i>n</i> ‾ <i>p</i>) per processor.

EXPERIMENTAL EVALUATION OF BSP PROGRAMMING LIBRARIES

The model of bulk-synchronous parallel computation (BSP) helps to implement portable general purpose algorithms while maintaining predictable performance on different parallel computers. Nevertheless, when programming in ‘BSP style’, the running time of the implementation of an algorithm can be very dependent on the underlying communication library. In this study, an overview of existing approaches to practical BSP programming in C/C++ or Fortran is given and benchmarks were run for the two main BSP-like communication libraries, the Oxford BSP Toolset and PUB. Furthermore, a memory efficient matrix multiplication algorithm was implemented and used to compare their performance on different parallel computers and to evaluate the compliance with predictions by theoretical results.

Parallel longest increasing subsequences in scalable time and memory

The longest increasing subsequence (LIS) problem is a classical problem in theoretical computer science and mathematics. Most existing parallel algorithms for this problem have very restrictive slackness conditions which prevent scalability to large numbers of processors. Other algorithms are scalable, but not work-optimal w.r.t. the fastest sequential algorithm for the LIS problem, which runs in time O(n log n) for n numbers in the comparison-based model. In this paper, we propose a new parallel algorithm for the LIS problem. Our algorithm solves the more general problem of semi-local comparison of permutation strings of length n in time O(n/1.5p) on p processors, has scalable communication cost of O(n/√p) and is synchronisation-efficient. Furthermore, we achieve scalable memory cost, requiring O(n/√p) of storage on each processor. When applied to LIS computation, this algorithm is superior to previous approaches since computation, communication, and memory costs are all scalable.

Analysis of 5’ gene regions reveals extraordinary conservation of novel non-coding sequences in a wide range of animals

BackgroundPhylogenetic footprinting is a comparative method based on the principle that functional sequence elements will acquire fewer mutations over time than non-functional sequences. Successful comparisons of distantly related species will thus yield highly important sequence elements likely to serve fundamental biological roles. RNA regulatory elements are less well understood than those in DNA. In this study we use the emerging model organism Nasonia vitripennis, a parasitic wasp, in a comparative analysis against 12 insect genomes to identify deeply conserved non-coding elements (CNEs) conserved in large groups of insects, with a focus on 5’ UTRs and promoter sequences.ResultsWe report the identification of 322 CNEs conserved across a broad range of insect orders. The identified regions are associated with regulatory and developmental genes, and contain short footprints revealing aspects of their likely function in translational regulation. The most ancient regions identified in our analysis were all found to overlap transcribed regions of genes, reflecting stronger conservation of translational regulatory elements than transcriptional elements. Further expanding sequence analyses to non-insect species we also report the discovery of, to our knowledge, the two oldest and most ubiquitous CNE’s yet described in the animal kingdom (700 MYA). These ancient conserved non-coding elements are associated with the two ribosomal stalk genes, RPLP1 and RPLP2, and were very likely functional in some of the earliest animals.ConclusionsWe report the identification of the most deeply conserved CNE’s found to date, and several other deeply conserved elements which are without exception, part of 5’ untranslated regions of transcripts, and occur in a number of key translational regulatory genes, highlighting translational regulation of translational regulators as a conserved feature of insect genomes.

Efficient longest common subsequence computation using bulk-synchronous parallelism

This paper presents performance results for parallel algorithms that compute the longest common subsequence of two strings. This algorithm is a representative of a class of algorithms that compute string to string distances and has computational complexity O(n 2 ). The parallel algorithm uses a variable grid size, runs in O(p) supersteps (synchronization phases) and has linear communication costs. We study this algorithm in BSP context, give runtime estimations and compare the predictions to experimental values measured on three different parallel architectures, using different BSP programming libraries and an efficient implementation for sequential computation. We find that using the BSP model and the appropriate optimized BSP library improves the performance over plain MPI, and that scalability can be improved by using a tuned grid size parameter.

Genomic plasticity and rapid host switching can promote the evolution of generalism: a case study in the zoonotic pathogen Campylobacter

Horizontal gene transfer accelerates bacterial adaptation to novel environments, allowing selection to act on genes that have evolved in multiple genetic backgrounds. This can lead to ecological specialization. However, little is known about how zoonotic bacteria maintain the ability to colonize multiple hosts whilst competing with specialists in the same niche. Here we develop a stochastic evolutionary model and show how genetic transfer of host segregating alleles, distributed as predicted for niche specifying genes, and the opportunity for host transition could interact to promote the emergence of host generalist lineages of the zoonotic bacterium Campylobacter. Using a modelling approach we show that increasing levels of homologous recombination enhance the efficiency with which selection can fix combinations of beneficial alleles, speeding adaptation. We then show how these predictions change in a multi-host system, with low levels of recombination, consistent with real r/m estimates, increasing the standing variation in the population, allowing a more effective response to changes in the selective landscape. Our analysis explains how observed gradients of host specialism and generalism can evolve in a multihost system through the transfer of ecologically important loci among coexisting strains.