Search

BACKGROUND Existing approaches for measuring hemostasis parameters require multiple platforms, can take hours to provide results, and generally require 1–25 mL of sample. We developed a diagnostic platform that allows comprehensive assessment of hemostatic parameters on a single instrument and provides results within 15 min using 0.04 mL of blood with minimal sample handling. METHODS T2 magnetic resonance (T2MR) was used to directly measure integrated reactions in whole blood samples by resolving multiple water relaxation times from distinct sample microenvironments. Clotting, clot contraction, and fibrinolysis stimulated by thrombin or tissue plasminogen activator, respectively, were measured. T2MR signals of clotting samples were compared with images produced by scanning electron microscopy and with standard reference methods for the following parameters: hematocrit, prothrombin time, clot strength, and platelet activity. RESULTS Application of T2MR methodology revealed conditions under which a unique T2MR signature appeared that corresponded with the formation of polyhedral erythrocytes, the dynamics and morphology of which are dependent on thrombin, fibrinogen, hematocrit, and platelet levels. We also showed that the T2MR platform can be used for precise and accurate measurements of hematocrit (%CV, 4.8%, R2 = 0.95), clotting time (%CV, 3.5%, R2 = 0.94), clot strength (R2 = 0.95), and platelet function (93% agreement with light transmission aggregometry). CONCLUSIONS This proof-of-concept study demonstrates that T2MR has the potential to provide rapid and sensitive identification of patients at risk for thrombosis or bleeding and to identify new biomarkers and therapeutic targets with a single, simple-to-employ analytic approach that may be suitable for routine use in both research and diverse clinical settings.

The sequence and structural conservation of folding transition states have been predicted on theoretical grounds. Using homologous sequence alignments of proteins previously characterized via coupled mutagenesis/kinetics studies, we tested these predictions experimentally. Only one of the six appropriately characterized proteins exhibits a statistically significant correlation between residues' roles in transition state structure and their evolutionary conservation. However, a significant correlation is observed between the contributions of individual sequence positions to the transition state structure across a set of homologous proteins. Thus the structure of the folding transition state ensemble appears to be more highly conserved than the specific interactions that stabilize it.

Multiple-complete-digest mapping is a DNA mapping technique based on complete-restriction-digest fingerprints of a set of clones that provides highly redundant coverage of the mapping target. The maps assembled from these fingerprints order both the clones and the restriction fragments. Maps are coordinated across three enzymes in the examples presented. Starting with yeast artificial chromosome contigs from the 7q31.3 and 7p14 regions of the human genome, we have produced cosmid-based maps spanning more than one million base pairs. Each yeast artificial chromosome is first subcloned into cosmids at a redundancy of ×15–30. Complete-digest fragments are electrophoresed on agarose gels, poststained, and imaged on a fluorescent scanner. Aberrant clones that are not representative of the underlying genome are rejected in the map construction process. Almost every restriction fragment is ordered, allowing selection of minimal tiling paths with clone-to-clone overlaps of only a few thousand base pairs. These maps demonstrate the practicality of applying the experimental and software-based steps in multiple-complete-digest mapping to a target of significant size and complexity. We present evidence that the maps are sufficiently accurate to validate both the clones selected for sequencing and the sequence assemblies obtained once these clones have been sequenced by a “shotgun” method.

The recent transition in gene expression analysis technology to ultra high-throughput cDNA sequencing provides a means for higher quantitation sensitivity across a wider dynamic range than previously possible. Sensitivity of detection is mostly a function of the sheer number of sequence reads generated. Typically, RNA is converted to cDNA using random hexamers and the cDNA is subsequently sequenced (RNA-Seq). With this approach, higher read numbers are generated for long transcripts as compared to short ones. This length bias necessitates the generation of very high read numbers to achieve sensitive quantitation of short, low-expressed genes. To eliminate this length bias, we have developed an ultra high-throughput sequencing approach where only a single read is generated for each transcript molecule (single-molecule sequencing Digital Gene Expression (smsDGE)). So, for example, equivalent quantitation accuracy of the yeast transcriptome can be achieved by smsDGE using only 25% of the reads that would be required using RNA-Seq. For sample preparation, RNA is first reverse-transcribed into single-stranded cDNA using oligo-dT as a primer. A poly-A tail is then added to the 3' ends of cDNA to facilitate the hybridization of the sample to the Helicos(®) single-molecule sequencing Flow-Cell to which a poly dT oligo serves as the substrate for subsequent sequencing by synthesis. No PCR, sample-size selection, or ligation steps are required, thus avoiding possible biases that may be introduced by such manipulations. Each tailed cDNA sample is injected into one of 50 flow-cell channels and sequenced on the Helicos(®) Genetic Analysis System. Thus, 50 samples are sequenced simultaneously generating 10-20 million sequence reads on average for each sample channel. The sequence reads can then be aligned to the reference of choice such as the transcriptome, for quantitation of known transcripts, or the genome for novel transcript discovery. This chapter provides a summary of the methods required for smsDGE.

The rapid adoption of high-throughput next generation sequence data in biological research is presenting a major challenge for sequence alignment tools—specifically, the efficient alignment of vast amounts of short reads to large references in the presence of differences arising from sequencing errors and biological sequence variations. To address this challenge, we developed a short read aligner for high-throughput sequencer data that is tolerant of errors or mutations of all types—namely, substitutions, deletions, and insertions. The aligner utilizes a multi-stage approach in which template-based indexing is used to identify candidate regions for alignment with dynamic programming. A template is a pair of gapped seeds, with one used with the read and one used with the reference. In this article, we focus on the development of template families that yield error-tolerant indexing up to a given error-budget. A general algorithm for finding those families is presented, and a recursive construction that creates families with higher error tolerance from ones with a lower error tolerance is developed.

We present single-molecule sequencing digital gene expression (smsDGE), a high-throughput, amplification-free method for accurate quantification of the full range of cellular polyadenylated RNA transcripts using a Helicos Genetic Analysis system. smsDGE involves a reverse-transcription and polyA-tailing sample preparation procedure followed by sequencing that generates a single read per transcript. We applied smsDGE to the transcriptome of Saccharomyces cerevisiae strain DBY746, using 6 of the available 50 channels in a single sequencing run, yielding on average 12 million aligned reads per channel. Using spiked-in RNA, accurate quantitative measurements were obtained over four orders of magnitude. High correlation was demonstrated across independent flow-cell channels, instrument runs and sample preparations. Transcript counting in smsDGE is highly efficient due to the representation of each transcript molecule by a single read. This efficiency, coupled with the high throughput enabled by the single-molecule sequencing platform, provides an alternative method for expression profiling.

The full promise of human genomics will be realized only when the genomes of thousands of individuals can be sequenced for comparative analysis. A reference sequence enables the use of short read length. We report an amplification-free method for determining the nucleotide sequence of more than 280,000 individual DNA molecules simultaneously. A DNA polymerase adds labeled nucleotides to surface-immobilized primer-template duplexes in stepwise fashion, and the asynchronous growth of individual DNA molecules was monitored by fluorescence imaging. Read lengths of >25 bases and equivalent phred software program quality scores approaching 30 were achieved. We used this method to sequence the M13 virus to an average depth of >150× and with 100% coverage; thus, we resequenced the M13 genome with high-sensitivity mutation detection. This demonstrates a strategy for high-throughput low-cost resequencing.

Locating protein coding regions in genomic DNA is a critical step in accessing the information generated by large scale sequencing projects. Current methods for gene detection depend on statistical measures of content differences between coding and noncoding DNA in addition to the recognition of promoters, splice sites, and other regulatory sites. Here we explore the potential value of recurrent amino acid sequence patterns 3-19 amino acids in length as a content statistic for use in gene finding approaches. A finite mixture model incorporating these patterns can partially discriminate protein sequences which have no (detectable) known homologs from randomized versions of these sequences, and from short (or = 50 amino acids) non-coding segments extracted from the S. cerevisiea genome. The mixture model derived scores for a collection of human exons were not correlated with the GENSCAN scores, suggesting that the addition of our protein pattern recognition module to current gene recognition programs may improve their performance.

Multiple Complete Digest (MCD) mapping is a method of determining the locations of restriction sites along a target DNA molecule. The resulting restriction map has many potential applications in DNA sequencing and genetics. In this work, we present a heuristic algorithm for fragment identification, a key step in the process of constructing an MCD map. Given measurements of the restriction fragment sizes from one or more complete digestions of each clone in a clone library covering the molecule to be mapped, the algorithm identifies groups of restriction fragments on different clones that correspond to the same region of the target DNA. Once these groups are correctly determined the desired map can be constructed by solving a system of simple linear inequalities. We demonstrate the effectiveness of our algorithm on real data provided by the Genome Center at the University of Washington.

Genetic and physical maps display the relative positions of objects or markers occurring within a target DNA molecule. In constructing maps, the primary objective is to determine the ordering of these objects. A further objective is to assign a coordinate to each object, indicating its distance from a reference end of the target molecule. This paper describes a computational method and a body of software for assigning coordinates to map objects, given a solution or partial solution to the ordering problem. We describe our method in the context of multiple–complete–digest (MCD) mapping, but it should be applicable to a variety of other mapping problems. Because of errors in the data or insufficient clone coverage to uniquely identify the true ordering of the map objects, a partial ordering is typically the best one can hope for. Once a partial ordering has been established, one often seeks to overlay a metric along the map to assess the distances between the map objects. This problem often proves intractable because of data errors such as erroneous local length measurements (e.g., large clone lengths on low-resolution physical maps). We present a solution to the coordinate assignment problem for MCD restriction-fragment mapping, in which a coordinated set of single-enzyme restriction maps are simultaneously constructed. We show that the coordinate assignment problem can be expressed as the solution of a system of linear constraints. If the linear system is free of inconsistencies, it can be solved using the standard Bellman–Ford algorithm. In the more typical case where the system is inconsistent, our program perturbs it to find a new consistent system of linear constraints, close to those of the given inconsistent system, using a modified Bellman–Ford algorithm. Examples are provided of simple map inconsistencies and the methods by which our program detects candidate data errors and directs the user to potential suspect regions of the map.

Abstract 1118 There are no currently available tests to rapidly assess and reliably identify both impaired hemostasis and hypercoagulable states, in part because of difficulties in measuring integrated reactions in whole blood using a single sensitive and clinically useful platform. Methods like T2 magnetic resonance (T2MR) can provide rich information from complex samples, such as changes in the blood during hemostasis, by measuring signals emanating from the hydrogen nuclei within the sample, primarily in water. We used a 14”x6”x7” portable instrument to measure changes in T2MR that provide a continuous report on the dynamically changing microscopic environment of water during coagulation of whole blood (WB), platelet-poor or platelet-rich plasma (PRP). In these initial foundational studies, we measured T2MR continuously over 20 mins using 34 μL blood samples from consented normal adult donors. We tested clotting of WB initiated by the addition of thrombin or kaolin + calcium. Platelet activation was achieved in WB by addition of ADP or arachidonic acid in the presence of reptilase and factor XIIIa with and without addition of the platelet inhibitors aspirin or 2-methylthioadenosine 5'-monophosphate (2-MeSAMP) and results were confirmed by standard platelet aggregometry. At normal platelet counts from 1.5–3×105/μL and normal hematocrit (HCT) from 38%-48%, T2MR gave two curves corresponding to: (1) water trapped within a retracted clot and (2) water in the surrounding liquid, i.e. serum (Fig. 1a). Platelet counts Our proof-of-principle studies show that T2MR technology can be applied to measurement of blood clotting across a range of hemostatic conditions. This single technology may be applicable to the study, diagnosis, and management of a spectrum of disorders that range from impaired hemostasis to hypercoagulable states. These T2MR studies represent the first application of this technology to hemostasis and thrombosis. Additional studies will be needed to develop a more complete understanding of the biochemical events measured by T2MR and to more fully explore its clinical utility. Figure 1. Examples of T2MR 3D surfaces for 34 μL of citrated whole blood mixed activated by adding a dried formulation of CaCl2 (11 mM) and kaolin ( Disclosures: Cines: T2 Biosystems: Research Funding. Lebedeva:T2 Biosystems: Research Funding. Massefski:T2 Biosystems: Employment. Papkov:T2 Biosystems: Employment. Thayer:T2 Biosystems: Employment. Lowery:T2 Biosystems: Employment.

Physical maps of the six smallest chromosomes of Saccharomyces cerevisiae are presented. In order of increasing size, they are chromosomes I, VI, III, IX, V and VIII, comprising 2.49 megabase pairs of DNA. The maps are based on the analysis of an overlapping set of lambda and cosmid clones. Overlaps between adjacent clones were recognized by shared restriction fragments produced by the combined action of EcoRI and HindIII. The average spacing between mapped cleavage sites is 2.6 kb. Five of the six chromosomes were mapped from end to end without discontinuities; a single internal gap remains in the map of chromosome IX. The reported maps span an estimated 97% of the DNA on the six chromosomes; nearly all the missing segments are telomeric. The maps are fully cross-correlated with the previously published SfiI/NotI map of the yeast genome by A. J. Link and M. V. Olson. They have also been cross-correlated with the yeast genetic map at 51 loci.