Using high-technology gene sequencing techniques on both bacteria and microbial eukaryotic organisms like fungi, nematodes and amoeba postmortem, the researchers were able to pinpoint time of mouse death after a 48-day period to within roughly four days. The results were even more accurate following an analysis at 34 days, correctly estimating the time of death within about three days, said Jessica Metcalf, a CU-Boulder postdoctoral researcher and first author on the study.
The paper on the subject was published Sept. 23, 2013, in the new online science and biomedical journal, eLIFE, a joint initiative of the Howard Hughes Medical Institute, the Max Planck Society and the Wellcome Trust Fund. The study was funded by the National Institute of Justice.
The researchers tracked microbial changes on the heads, torsos, body cavities and associated grave soil of 40 mice at eight different time points over the 48-day study. The stages after death include the “fresh” stage before decomposition, followed by “active decay” that includes bloating and subsequent body cavity rupture, followed by “advanced decay,” said Chaminade University forensic scientist David Carter, a co-author on the study.
“At each time point that we sampled, we saw similar microbiome patterns on the individual mice and similar biochemical changes in the grave soil,” said Laura Parfrey, a former CU-Boulder postdoctoral fellow and now a faculty member at the University of British Columbia who is a microbial and eukaryotic expert. “And although there were dramatic changes in the abundance and distribution of bacteria over the course of the study, we saw a surprising amount of consistency between individual mice microbes between the time points -- something we were hoping for.”
As part of the project, the researchers also charted “blooms” of a common soil-dwelling nematode well known for consuming bacterial biomass that occurred at roughly the same time on individual mice during the decay period. “The nematodes seem to be responding to increases in bacterial biomass during the early decomposition process, an interesting finding from a community ecology standpoint,” said Metcalf.
“This work shows that your microbiome is not just important while you’re alive,” said CU-Boulder Associate Professor Rob Knight, the corresponding study author who runs the lab where the experiments took place. “It might also be important after you're dead.”
In this book, an impressive array of expert authors highlight and review current advances in genome analysis. This volume provides an invaluable, up-to-date and comprehensive overview of the methods currently employed for next-generation sequencing (NGS) data analysis, highlights their problems and limitations, demonstrates the applications and indicates the developing trends in various fields of genome research. The first part of the book is devoted to the methods and applications that arose from, or were significantly advanced by, NGS technologies: the identification of structural variation from DNA-seq data; whole-transcriptome analysis and discovery of small interfering RNAs (siRNAs) from RNA-seq data; motif finding in promoter regions, enhancer prediction and nucleosome sequence code discovery from ChiP-Seq data; identification of methylation patterns in cancer from MeDIP-seq data; transposon identification in NGS data; metagenomics and metatranscriptomics; NGS of viral communities; and causes and consequences of genome instabilities. The second part is devoted to the field of RNA biology with the last three chapters devoted to computational methods of RNA structure prediction including context-free grammar applications.
Next-generation sequencing allows detection of minor variants in a heterogeneous sample. However, errors in PCR and sequencing pose limits on its sensitivity. A group at University of Washington developed a method, called Duplex Sequencing, to dramatically improve accuracy by sequencing both strands of each DNA duplex. Mutations that are detected in the consensus sequence of one strand but not the other are discounted as technical errors.
The authors adopted the method to Illumina sequencing. It involves the use of modified adaptors that have a tag with random sequence attached. After ligation of these modified adaptors, each duplex DNA fragment is flanked by two different tags and subjected to paired-end sequencing. Sequences of the same duplex from the complementary strands can therefore be uniquely identified by having the same tags on either ends. Comparing sequences of the two strands allows identification of true mutations. The authors estimated that Duplex sequencing has a theoretical background error rate of less than one per 10^9 nucleotides sequenced.
Editorial from The New England Journal of Medicine — Next-Generation Sequencing for Clinical Diagnostics (Next-Generation Sequencing for Clinical Diagnostics—commentary by @Personal_RX_WI in @NEJM on huge @bcmhouston study
Although I often write about the challenges of next-gen sequencing, it occurred to me that these technologies have reached a certain point of maturity. Thanks to the happy co-evolution of technological and informatics ...
A project to map the microbes present in the digestive systems of fish species holds promise for monitoring the presence of Asian carp in Chicago area waterways and ultimately preventing their spread, according to a study published in Nature's ISME...
Scientists routinely seek to reprogram bacteria to produce proteins for drugs, biofuels and more, but they have struggled to get those bugs to follow orders. But a hidden feature of the genetic code, it turns out, could get bugs with the program. The feature controls how much of the desired protein bacteria produce, a team from the Wyss Institute for Biologically Inspired Engineering at Harvard University reported in the September 26 online issue of Science.
The findings could be a boon for biotechnologists, and they could help synthetic biologists reprogram bacteria to make new drugs and biological devices.
By combining high-speed "next-generation" DNA sequencing and DNA synthesis technologies, Sri Kosuri, Ph.D., a Wyss Institute staff scientist, George Church, Ph.D., a core faculty member at the Wyss Institute and professor of genetics at Harvard Medical School, and Daniel Goodman, a Wyss Institute graduate research fellow, found that using more rare words, or codons, near the start of a gene removes roadblocks to protein production.
"Now that we understand how rare codons control gene expression, we can better predict how to synthesize genes that make enzymes, drugs, or whatever you want to make in a cell," Kosuri said.
To produce a protein, a cell must first make working copies of the gene encoding it. These copies, called messenger RNA (mRNA), consist of a specific string of words, or codons. Each codon represents one of the 20 different amino acids that cells use to assemble proteins. But since the cell uses 61 codons to represent 20 amino acids, many codons have synonyms that represent the same amino acid.
In bacteria, as in books, some words are used more often than others, and molecular biologists have noticed over the last few years that rare codons appear more frequently near the start of a gene. What's more, genes whose opening sequences have more rare codons produce more protein than genes whose opening sequences do not.
No one knew for sure why rare codons had these effects, but many biologists suspected that they function as a highway on-ramp for ribosomes, the molecular machines that build proteins. According to this idea, called the codon ramp hypothesis, ribosomes wait on the on-ramp, then accelerate slowly along the mRNA highway, allowing the cell to make proteins with all deliberate speed. But without the on-ramp, the ribosomes gun it down the mRNA highway, then collide like bumper cars, causing traffic accidents that slow protein production. Other biologists suspected rare codons acted via different mechanisms. These include mRNA folding, which could create roadblocks for ribosomes that block the highway and slow protein production.
Summary: The rapid growth of DNA sequencing throughput in recent years implies that graphical interfaces for viewing and correcting errors must now handle large numbers of reads, efficiently pinpoint regions of interest and automate as many tasks as possible. We have adapted consedto reflect this. To allow full-feature editing of large datasets while keeping memory requirements low, we developed a viewer, bamScape, that reads billion-read BAM files, identifies and displays problem areas for user review and launches the consed graphical editor on user-selected regions, allowing, in addition to longstanding consed capabilities such as assembly editing, a variety of new features including direct editing of the reference sequence, variant and error detection, display of annotation tracks and the ability to simultaneously process a group of reads. Many batch processing capabilities have been added.
Today's Medical Developments Next-Generation Sequencing Today's Medical Developments Next-generation sequencing (NGS) has been touted as the game-changing technology for the field of diagnostics and personalized medicine.
NEW YORK (GenomeWeb News) – Advanced Biological Laboratories said today it signed a non-exclusive agreement with Roche Diagnostics for the promotion of certain ABL products. In particular, the deal is aimed at ...
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