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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Prediction of Specificity of α-Conotoxins to Subtypes of Human Nicotinic Acetylcholine Receptors with Semi-supervised Machine Learning

Conotoxins are a family of highly toxic neurotoxins composed of cysteine-rich peptides produced by marine cone snails. The most lethal cone snail species to humans is Conus geographus, with fatality rates of up to ∼65% from a single sting, which is caused mostly by the activity of α-conotoxins against human nicotinic acetylcholine receptors (nAChRs). While sequence-based machine learning (ML) classifiers have been trained to identify targets of conotoxins binding voltage-gated ion channels, no ML model has been built to predict the subtype-specific nAChR targets of α-conotoxins. Here, we trained an ML model in a semi-supervised manner to predict the specificity of α-conotoxin binding toward different human nAChR subtypes to overcome the challenge of limited data in subtype-specific nAChR targets of α-conotoxins and the issue that one α-conotoxin can bind multiple nAChR subtypes with high selectivity. We considered additional features of sequences of α-conotoxins in training our ML model, including the secondary structure propensities and electrostatic properties, which resulted in better prediction capability for the ML model. Notably, we identify that most α-conotoxins bind to α3β2, α1γδ, and α7 subtypes of human nAChRs. Our findings from this study provide a framework for predicting targets of various kinds of toxins.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Unlocking the Microbiome of the International Space Station

With the start of human occupation more than 22 years ago, the microbiome of International Space Station (ISS) has been monitored to assess risk to both crew and craft. Historically, this monitoring has been achieved through onboard culture and ground-based analyses. Data spanning this timeframe are descriptive of a semi-closed, human occupied environment with associations to crew changes and process escapes within the environmental control and life support systems. While this approach has served to provide alerts to anomalies and overall confidence in the controls in place, the data are limited to the media type and growth conditions used. The bias toward the detection of culturable organisms has depicted an overall lack in biodiversity. As NASA leaves the ISS to focus on exploration, it is critical to fully understand its microbiome and its possible association to the noted positive influence on crew and vehicle health. The implementation of culture-independent, nanopore sequencing-based studies, both onboard the ISS and with returned ground samples, is revealing a more thorough depiction of the microbiome. As noted with pervious culture-based data, there is a common core microbiome across time and location, but key distinct areas of greater diversity exist. Through further investigation, these areas are emerging as unique ecological niches, potentially resulting in environmentally driven microbial selection. Moreover, the presence of some noted taxa within these unique locations has implications for crew health, planetary protection, and controls used in future spacecraft systems. The ability to perform in situ profiling of the ISS microbiome is transforming how NASA assesses risk and is a critical tool towards monitoring the establishment of the environmental microbiome in exploration spacecraft.

Sarah Stahl-Rommel↗

DOE OSTI2016

Impact of Organic Carbon Electron Donors on Microbial Community Development under Iron- and Sulfate-Reducing Conditions

Although iron- and sulfate-reducing bacteria in subsurface environments have crucial roles in biogeochemical cycling of C, Fe, and S, how specific electron donors impact the compositional structure and activity of native iron- and/or sulfate-reducing communities is largely unknown. To understand this better, we created bicarbonate-buffered batch systems in duplicate with three different electron donors (acetate, lactate, or glucose) paired with ferrihydrite and sulfate as the electron acceptors and inoculated them with subsurface sediment as the microbial inoculum. Sulfate and ferrihydrite reduction occurred simultaneously and were faster with lactate than with acetate. 16S rRNA-based sequence analysis of the communities over time revealed that Desulfotomaculum was the major driver for sulfate reduction coupled with propionate oxidation in lactate-amended incubations. The reduction of sulfate resulted in sulfide production and subsequent abiotic reduction of ferrihydrite. In contrast, glucose promoted faster reduction of ferrihydrite, but without reduction of sulfate. Interestingly, the glucose-amended incubations led to two different biogeochemical trajectories among replicate bottles that resulted in distinct coloration (white and brown). The two outcomes in geochemical evolution might be due to the stochastic evolution of the microbial communities or subtle differences in the initial composition of the fermenting microbial community and its development via the use of different glucose fermentation pathways available within the community. Synchrotron-based x-ray analysis indicated that siderite and amorphous Fe(II) were formed in the replicate bottles with glucose, while ferrous sulfide and vivianite were formed with lactate or acetate. As a result, these data sets reveal that use of different C utilization pathways projects significant changes in microbial community composition over time that uniquely impact both the geochemistry and mineralogy of subsurface environments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Deep Impact Sequence Planning Using Multi-Mission Adaptable Planning Tools With Integrated Spacecraft Models

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

Deep Impact Mission↗

NASA NTRS2015

Methodology to Define Delivery Accuracy Under Current Day ATC Operations

In order to enable arrival management concepts and solutions in a NextGen environment, ground- based sequencing and scheduling functions have been developed to support metering operations in the National Airspace System. These sequencing and scheduling algorithms as well as tools are designed to aid air traffic controllers in developing an overall arrival strategy. The ground systems being developed will support the management of aircraft to their Scheduled Times of Arrival (STAs) at flow-constrained meter points. This paper presents a methodology for determining the undelayed delivery accuracy for current day air traffic control operations. This new method analyzes the undelayed delivery accuracy at meter points in order to understand changes of desired flow rates as well as enabling definition of metrics that will allow near-future ground automation tools to successfully achieve desired separation at the meter points. This enables aircraft to meet their STAs while performing high precision arrivals. The research presents a possible implementation that would allow delivery performance of current tools to be estimated and delivery accuracy requirements for future tools to be defined, which allows analysis of Estimated Time of Arrival (ETA) accuracy for Time-Based Flow Management (TBFM) and the FAA's Traffic Management Advisor (TMA). TMA is a deployed system that generates scheduled time-of-arrival constraints for en- route air traffic controllers in the US. This new method of automated analysis provides a repeatable evaluation of the delay metrics for current day traffic, new releases of TMA, implementation of different tools, and across different airspace environments. This method utilizes a wide set of data from the Operational TMA-TBFM Repository (OTTR) system, which processes raw data collected by the FAA from operational TMA systems at all ARTCCs in the nation. The OTTR system generates daily reports concerning ATC status, intent and actions. Due to its availability, ease of use, and vast collection of data across several airspaces it was determined that the OTTR data set would be the best method to utilize moving forward with this analysis. The particular variables needed for further analysis were determined along with the necessary OTTR reports, by working closely with the repository team additional analysis reports were developed that provided key ETA and STA information at the freeze horizon. One major benefit of the OTTR data is that using the correct reports the data across several airports could be analyzed over large periods of time. The OTTR data processes the TBFM data daily and is stored in various formats across several airspaces. This allowed us to develop our own parsing methods and raw data processing that would not rely on other computationally expensive tools that perform more in depth analysis of similar sets of data. The majority of this work consisted of the development of the ability to filter flights to create a subset of flights that could be considered undelayed, which is defined as a flight at the freeze horizon with an ETA and STA difference that was minimal or close to zero. This was a broad method that allowed the consideration of a large data set which consisted of all the traffic across a two month period in 2013, the hottest and coldest months, arriving into four airports: George Bush Intercontinental, Denver International, Los Angeles International, and Phoenix Sky Harbor.

delivery accuracy↗

DOE OSTI2020

Characterizing natural fractures and sub-seismic faults for well completion of Marcellus shale in the MSEEL Consortium project, West Virginia, USA

The Middle Devonian Marcellus shale play has emerged as a major world-class hydrocarbon accumulation and represents one of the largest and most prolific shale plays in the world. According to many outcrop studies in the region, natural fractures are well developed in the Marcellus Shale. However, evaluating fractures in the subsurface is often a significant challenge due to a lack of sufficient data. Therefore, in the Marcellus Shale Energy and Environment Laboratory (MSEEL) consortium project, significant efforts have been made to acquire high-quality image logs in the Marcellus laterals. The project provided tremendous opportunities to characterize the natural fractures and sub-seismic faults and to evaluate their impact on well stimulation. In this study, about 70,000 ft of acquired high-resolution logging while drilling (LWD) acoustic images from five long laterals located in Monongalia County, West Virginia, were processed and interpreted. In addition, the study used high-quality micro-resistivity images from a pilot well, allowing the evaluation of natural fractures in the entire Marcellus vertical sequence. Based on the available acoustic images, the natural fractures were classified into three basic categories: high-amplitude fractures, low-amplitude fractures, and faults. Further, larger open fractures can also be determined when a low-amplitude fracture is evident on caliper images. The fractures in the Marcellus usually have a medium to high angle dip; however, multiple fracture sets in terms of strike orientation were clearly observed in all the laterals. The fracture set with a strike at NE-SW (or 60-240 deg) seems to be the predominant one in all the wells. A few other sets, including those with N-S, NWW-SEE, and E-W strikes, were also observed. Several sub-seismic faults, with mostly a low dip angle and a NE-SW strike, have also been seen in two of the laterals. The fracture density is variable across all the laterals, ranging from very low (or none) to very high (up to 5 fractures per ft). The average fracture density for all the laterals is about 1 fracture per 10 ft. In the vertical sequence, the natural fracture development showed a clear preference for shale or shaly facies over carbonate-rich or thin limestone layers. The interpreted fracture and fault data were used as input data for the stimulation design with the purpose of better understanding the fractures’ impact on well stimulation. Production data from the laterals were also used to evaluate the natural fractures’ influence on well performance. The quality image database and the consistent interpretation results for the entire project enabled a systematic approach to characterizing fractures and, more importantly, to evaluating the impact of fractures on well stimulation and production.

03 NATURAL GAS↗

DOE OSTI2018

Small RNA profiling of low biomass samples: identification and removal of contaminants

Here, sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. DNA contamination has been previously reported, yet contamination with RNA is usually considered to be very unlikely due to its inherent instability. Small RNAs (sRNAs) identified in tissues and bodily fluids, such as blood plasma, have implications for physiology and pathology, and therefore the potential to act as disease biomarkers. Thus, the possibility for RNA contaminants demands careful evaluation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2012

Molecular Technique to Understand Deep Microbial Diversity

Current sequencing-based and DNA microarray techniques to study microbial diversity are based on an initial PCR (polymerase chain reaction) amplification step. However, a number of factors are known to bias PCR amplification and jeopardize the true representation of bacterial diversity. PCR amplification of the minor template appears to be suppressed by the exponential amplification of the more abundant template. It is widely acknowledged among environmental molecular microbiologists that genetic biosignatures identified from an environment only represent the most dominant populations. The technological bottleneck has overlooked the presence of the less abundant minority population, and underestimated their role in the ecosystem maintenance. To generate PCR amplicons for subsequent diversity analysis, bacterial l6S rRNA genes are amplified by PCR using universal primers. Two distinct PCR regimes are employed in parallel: one using normal and the other using biotinlabeled universal primers. PCR products obtained with biotin-labeled primers are mixed with streptavidin-labeled magnetic beads and selectively captured in the presence of a magnetic field. Less-abundant DNA templates that fail to amplify in this first round of PCR amplification are subjected to a second round of PCR using normal universal primers. These PCR products are then subjected to downstream diversity analyses such as conventional cloning and sequencing. A second round of PCR amplified the minority population and completed the deep diversity picture of the environmental sample.

Vaishampayan, Parag A.↗

NASA NTRS2002

A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.caltech.edu/~mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the beta-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentrotus purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of the model are greatly facilitated by interspecific computational sequence comparison, which affords a rapid identification of likely cis-regulatory elements in advance of experimental analysis. The network specifies genomically encoded regulatory processes between early cleavage and gastrula stages. These control the specification of the micromere lineage and of the initial veg(2) endomesodermal domain; the blastula-stage separation of the central veg(2) mesodermal domain (i.e., the secondary mesenchyme progenitor field) from the peripheral veg(2) endodermal domain; the stabilization of specification state within these domains; and activation of some downstream differentiation genes. Each of the temporal-spatial phases of specification is represented in a subelement of the network model, that treats regulatory events within the relevant embryonic nuclei at particular stages. (c) 2002 Elsevier Science (USA).

Non-NASA Center↗

DOE OSTI2025

UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.

Xue, Bo [Plant Resilience Institute Michigan State↗

DOE OSTI2018

Not as easy as π: An insertional residue does not explain the π‐helix gain‐of‐function in two‐component FMN reductases

Abstract The π‐helix located at the tetramer interface of two‐component FMN‐dependent reductases contributes to the structural divergence from canonical FMN‐bound reductases within the NADPH:FMN reductase family. The π‐helix in the SsuE FMN‐dependent reductase of the alkanesulfonate monooxygenase system has been proposed to be generated by the insertion of a Tyr residue in the conserved α4‐helix. Variants of Tyr118 were generated, and their X‐ray crystal structures determined, to evaluate how these alterations affect the structural integrity of the π‐helix. The structure of the Y118A SsuE π‐helix was converted to an α‐helix, similar to the FMN‐bound members of the NADPH:FMN reductase family. Although the π‐helix was altered, the FMN binding region remained unchanged. Conversely, deletion of Tyr118 disrupted the secondary structural properties of the π‐helix, generating a random coil region in the middle of helix 4. Both the Y118A and Δ118 SsuE SsuE variants crystallize as a dimer. The MsuE FMN reductase involved in the desulfonation of methanesulfonates is structurally similar to SsuE, but the π‐helix contains a His insertional residue. Exchanging the π‐helix insertional residue of each enzyme did not result in equivalent kinetic properties. Structure‐based sequence analysis further demonstrated the presence of a similar Tyr residue in an FMN‐bound reductase in the NADPH:FMN reductase family that is not sufficient to generate a π‐helix. Results from the structural and functional studies of the FMN‐dependent reductases suggest that the insertional residue alone is not solely responsible for generating the π‐helix, and additional structural adaptions occur to provide the altered gain of function.

McFarlane, Jeffrey S.↗

DOE OSTI2017

A transcriptome-SNP-derived linkage map of Apios americana (potato bean) provides insights about genome re-organization and synteny conservation in the phaseoloid legumes

Apios ( Apios americana ; “apios”), a tuberous perennial legume in the Phaseoleae tribe, was widely used as a food by Native Americans. Work in the last 40 years has led to several improved breeding lines. Aspects of the pollination biology (complex floral structure and tripping mechanism) have made controlled crosses difficult, and the previous reports indicated that the plant is likely primarily an outcrosser. We used a pseudo-testcross strategy to construct a genetic map specific to the maternal parent. The map was built using single-nucleotide polymorphism markers identified by comparing the expressed sequences of individuals in the mapping population against a de novo maternal reference transcriptome assembly. The apios map consists of 11 linkage groups and 1121 recombinationally distinct loci, covering ~ 938.6 cM. By sequencing the transcriptomes of all potential pollen parents, we were able to identify the probable pollen donors and to discover new aspects of the pollination biology in apios. No selfing was observed, but multiple pollen parents were seen within individual pods. Comparisons with genome sequences in other species in the Phaseoleae showed extended synteny for most apios linkage groups. This synteny supports the robustness of the map, and also sheds light on the history of the Phaseoleae, as apios is relatively early diverging in this tribe. We detected a translocation event that separates apios and two Vigna species from Phaseolus vulgaris and Glycine max. This apios mapping work provides a general protocol for sequencing-based construction of high-density linkage maps in outcrossing species with heterogeneous pollen parents.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Extracellular DNA Alters Detection of Subtle Bacterial Responses to Soil Rewetting

Microbial communities are often characterized using DNA-based sequencing, but these approaches also capture extracellular DNA (exDNA) released from dead cells, potentially altering inference about microbial responses to environmental change. This may be especially important during pulse disturbances, such as soil drying–rewetting, which can increase microbial mortality and transient necromass pools. We assessed whether exDNA altered inference about bacterial responses to drying–rewetting (an 80 mm simulated rainfall event following a 28-day drought) in conventionally tilled corn and perennial switchgrass soils. We quantified bacterial abundance (16 S rRNA gene copies), alpha diversity, and community composition in paired soil samples with exDNA included (+ exDNA) and in samples treated with propidium monoazide (PMAxx) to reduce amplification of exDNA (− exDNA). At our level of replication (n = 4), PMAxx treatment did not significantly alter overall temporal response patterns (i.e., no significant main effect of DNA treatment or DNA × time interaction). However, PMAxx treatment increased sensitivity to detect some pairwise temporal changes in bacterial abundance and community composition in corn soils following rewetting. exDNA pools were proportionally highest immediately after rewetting in corn soils, suggesting transient extracellular DNA may contribute to masking during disturbance recovery. In contrast, PMAxx treatment had comparatively small effects in switchgrass soils, which exhibited weaker temporal responses overall. Inclusion of exDNA also changed which taxa appeared most responsive to rewetting. Together, our results suggest that exDNA does not uniformly bias soil microbial inference, but may reduce detectability of subtle disturbance-driven shifts in certain soils. Future studies should advance knowledge of microbial turnover and necromass dynamics, particularly using multiple complementary methods, to help predict when exDNA is most likely to influence ecological inference.

drying-rewetting↗

DOE OSTI2017

Combining Hadoop with MPI to Solve Metagenomics Problems that are both Data- and Compute-intensive

Metagenomics, the study of all microbial species cohabitants in an environment, usually produces large amount of sequence data varying from several GBs to a few TBs. Analyzing metagenomics data includes both data-intensive and compute-intensive steps, making the entire process hard to scale. Here we aim to optimize a metagenomics application that partitions the shortgun metagenomics sequences based on their species of origin. Our solution combines MapReduce-based BioPig analytic toolkit with MPI to provide scalability in respective to both data and compute. We also made some improvements to the existing BioPig toolkit by using simplified data types and compressed k-mer storage. These optimizations leads up to 193× speedup for the computing-intensive step and 9.6× speedup over the entire pipeline. Our optimized application is also capable of processing datasets that are 16 times larger on the same hardware platform. These conclusions indicate integrating heterogeneous technologies such as Hadoop and MPI is quite efficient to solve large genomics problems that are both data-intensive and compute-intensive.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Variations of physical and chemical characteristics of biomass reduce equipment utilization and increase operational costs of biomass processing. Biomass processing facilities use sensors to monitor the changes in biomass characteristics. Integrating sensory data into the operational decisions in biomass processing will increase its flexibility to the changing biomass conditions. In this paper, we propose a multi-stage stochastic programming model that minimizes the expected operational costs by identifying the initial inventory level and creating an operational decision policy for equipment speed settings. These policies take the sensory information data and the current biomass inventory level as inputs to dynamically adjust inventory levels and equipment settings according to the changes in the biomass' characteristics. We ensure that a prescribed target reactor utilization is consistently achieved by penalizing the violation of the target reactor feeding rate. A case study is developed using real-world data collected at Idaho National Laboratory's biomass processing facility. We show the value of multi-stage stochastic programming from an extensive computational experiment. Our sensitivity analysis indicates that updating the infeed rate of the system, the processing speed of equipment, and bale sequencing based on the moisture level of biomass improves the processing rate of the reactor and reduces operating costs.

09 BIOMASS FUELS↗

DOE OSTI2016

The Sphagnum Genome Project: a new model for ecological and evolutionary genomics. In: Genomes and Evolution of Charophytes, Bryophytes, Club Mosses and Ferns

The inception of the Sphagnum (peat moss) genome project marks the first plant-based sequencing project aimed specifically at carbon cycling genomics in a plant system relevant to ecological and evolutionary genomics. Sphagnum provides considerable intra- and interspecific variation at the nucleotide level, and in physiology, morphology, net production, decomposition and carbon accumulation (peat formation). Because of the large number of peat moss species, their diversity in mating systems, and clear patterns of niche differentiation, Sphagnum provides an exceptionally valuable complement to Physcomitrella patens and Ceratodon purpureus as moss models for genomic research. Here we review the organismal biology of Sphagnum including phylogeny, life cycle, mating systems, ecology and niche differentiation. We include the current state of Sphagnum genomic resources, in vitro methods and germplasm. A use-case is provided to address questions concerning epigenetics and reproduction.

Shaw, AJ↗

DOE OSTI2018

An atomistic building block description of C-S-H - Towards a realistic C-S-H model

Understanding the atomistic structure of Calcium silicate hydrate (C-S-H), the main product of cement hydration, is of paramount importance to better formulate sustainable cement. The existing atomistic models are not in total agreement with experimental results and fail to explain the nanosized nature of C-S-H. Here, we present a new approach for describing the complexity of these structures at the molecular level, enabling a detailed comparison of C-S-H models. The new methodology encodes a full, large scale atomistic C-S-H structure by a simple, readable string of characters, similar to the way the base sequence in DNA encodes a vast range of different proteins. We then use the methodology to assess 14 Å tobermorite-defect structures and their stabilities using DFT and classical molecular dynamics. Finally we highlight how the model may be extended to develop reliable atomistic C-S-H models for a range of Ca/Si ratios and conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

MjCyc: Rediscovering the pathway-genome landscape of the first sequenced archaeon, Methanocaldococcus (Methanococcus) jannaschii

The genome of Methanocaldococcus (Methanococcus) jannaschii DSM 2661 was the first Archaeal genome to be sequenced in 1996. Subsequent sequence-based annotation cycles led to its first metabolic reconstruction in 2005. Leveraging new experimental results and function assignments, we have now re-annotated M. jannaschii, creating an updated resource with novel information and testable predictions in a pathway-genome database available at BioCyc.org. This reannotation effort has resulted in 652 function assignments with enzyme roles, accounting for a third of the total protein-coding entries for this genome. The updated resource includes 883 reactions, 540 enzymes, and 142 individual pathways. Despite notable progress in computational genomics, more than a third of the genome remains functionally uncharacterized. The publicly available MjCyc pathway-genome database holds great potential for the wider community to conduct research on the biology of methanogenic Archaea.

59 BASIC BIOLOGICAL SCIENCES↗