scholarly journals How to get your goat: automated identification of species from MALDI-ToF spectra

2020 ◽  
Vol 36 (12) ◽  
pp. 3719-3725
Author(s):  
Simon Hickinbotham ◽  
Sarah Fiddyment ◽  
Timothy L Stinson ◽  
Matthew J Collins
Keyword(s):  
Sequence Data ◽  
New Method ◽  
Supplementary Information ◽  
Automated Identification ◽  
Confidence Measure ◽  
Maldi Tof ◽  
Automated Method ◽  
Identification Of Species ◽  
Quantifiable Level

Abstract Motivation Classification of archaeological animal samples is commonly achieved via manual examination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) spectra. This is a time-consuming process which requires significant training and which does not produce a measure of confidence in the classification. We present a new, automated method for arriving at a classification of a MALDI-ToF sample, provided the collagen sequences for each candidate species are available. The approach derives a set of peptide masses from the sequence data for comparison with the sample data, which is carried out by cross-correlation. A novel way of combining evidence from multiple marker peptides is used to interpret the raw alignments and arrive at a classification with an associated confidence measure. Results To illustrate the efficacy of the approach, we tested the new method with a previously published classification of parchment folia from a copy of the Gospel of Luke, produced around 1120 C.E. by scribes at St Augustine’s Abbey in Canterbury, UK. In total, 80 of the 81 samples were given identical classifications by both methods. In addition, the new method gives a quantifiable level of confidence in each classification. Availability and implementation The software can be found at https://github.com/bioarch-sjh/bacollite, and can be installed in R using devtools. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals An iterative and automated computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic samples

2019 ◽  
Author(s):  
Mathias Kuhring ◽  
Joerg Doellinger ◽  
Andreas Nitsche ◽  
Thilo Muth ◽  
Bernhard Y. Renard
Keyword(s):  
Statistical Power ◽  
Sequence Data ◽  
A Priori ◽  
Search Space ◽  
Strain Level ◽  
Reference Sequence ◽  
Viral Origin ◽  
Identification Of Species ◽  
Taxonomic Assignments

AbstractUntargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes.We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to improve candidate confidence.We apply our iterative workflow on several samples of bacterial and viral origin. In comparison to non-iterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted and continuously growing sequence resources such as the NCBI databases and is available under open-source license at https://gitlab.com/rki_bioinformatics.

Chicken Pituitary Glycoproteins: New Isolation Method

1999 ◽  
Vol 64 (9) ◽  
pp. 1510-1516
Author(s):  
Helena Ryšlavá ◽  
Jana Krešlová ◽  
Jana Barthová ◽  
Tomislav Barth
Keyword(s):  
Mass Spectrometry ◽  
Luteinizing Hormone ◽  
New Method ◽  
Hormonal Activity ◽  
Isolation Method ◽  
Molecular Weights ◽  
Testosterone Production ◽  
Maldi Tof ◽  
Tryptic Cleavage

A new method for isolation of glycoproteins from chicken pituitaries was applied. The procedure consist of chromatography on ConA-Sepharose and by HPLC on S Hyper D and Vydac C4 columns. The hormonal activity of the glycoproteins was tested by determining their stimulatory effect on cAMP or testosterone production. Molecular weights of the products of tryptic cleavage of the hormone were determined using mass spectrometry (MALDI TOF). A comparison of the values obtained with theory shows that the protein is the β-unit of chicken luteinizing hormone.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

Automation and validation of a MALDI-TOF MS (Mass-Fix) replacement of immunofixation electrophoresis in the clinical lab

2021 ◽  
Vol 59 (1) ◽  
pp. 155-163
Author(s):  
Mindy Kohlhagen ◽  
Surendra Dasari ◽  
Maria Willrich ◽  
MeLea Hetrick ◽  
Brian Netzel ◽  
...  
Keyword(s):  
Limit Of Detection ◽  
Turnaround Time ◽  
Automated System ◽  
Serum Samples ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Automated Method ◽  
Positive Specimen ◽  
Specimen Identification ◽  
Tof Ms

AbstractObjectivesA matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) method (Mass-Fix) as a replacement for gel-based immunofixation (IFE) has been recently described. To utilize Mass-Fix clinically, a validated automated method was required. Our aim was to automate the pre-analytical processing, improve positive specimen identification and ergonomics, reduce paper data storage and increase resource utilization without increasing turnaround time.MethodsSerum samples were batched and loaded onto a liquid handler along with reagents and a barcoded sample plate. The pre-analytical steps included: (1) Plating immunopurification beads. (2) Adding 10 μl of serum. (3) Bead washing. (4) Eluting the immunoglobulins (Igs), and reducing to separate the heavy and light Ig chains. The resulting plate was transferred to a second low-volume liquid handler for MALDI plate spotting. MALDI-TOF mass spectra were collected. Integrated in-house developed software was utilized for sample tracking, driving data acquisition, data analysis, history tracking, and result reporting. A total of 1,029 residual serum samples were run using the automated system and results were compared to prior electrophoretic results.ResultsThe automated Mass-Fix method was capable of meeting the validation requirements of concordance with IFE, limit of detection (LOD), sample stability and reproducibility with a low repeat rate. Automation and integrated software allowed a single user to process 320 samples in an 8 h shift. Software display facilitated identification of monoclonal proteins. Additionally, the process maintains positive specimen identification, reduces manual pipetting, allows for paper free tracking, and does not significantly impact turnaround time (TAT).ConclusionsMass-Fix is ready for implementation in a high-throughput clinical laboratory.

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

scholarly journals Sequence data from isolated lichen-associated melanized fungi enhance delimitation of two new lineages within Chaetothyriomycetidae

2021 ◽  
Vol 20 (7) ◽  
pp. 911-927
Author(s):  
Lucia Muggia ◽  
Yu Quan ◽  
Cécile Gueidan ◽  
Abdullah M. S. Al-Hatmi ◽  
Martin Grube ◽  
...  
Keyword(s):  
Sequence Data ◽  
Single Species ◽  
Sister Group ◽  
Asexual Propagation ◽  
Dna Sequence Data ◽  
Wide Range ◽  
The Family ◽  
Rock Inhabiting Fungi ◽  
Stable Habitat

AbstractLichen thalli provide a long-lived and stable habitat for colonization by a wide range of microorganisms. Increased interest in these lichen-associated microbial communities has revealed an impressive diversity of fungi, including several novel lineages which still await formal taxonomic recognition. Among these, members of the Eurotiomycetes and Dothideomycetes usually occur asymptomatically in the lichen thalli, even if they share ancestry with fungi that may be parasitic on their host. Mycelia of the isolates are characterized by melanized cell walls and the fungi display exclusively asexual propagation. Their taxonomic placement requires, therefore, the use of DNA sequence data. Here, we consider recently published sequence data from lichen-associated fungi and characterize and formally describe two new, individually monophyletic lineages at family, genus, and species levels. The Pleostigmataceae fam. nov. and Melanina gen. nov. both comprise rock-inhabiting fungi that associate with epilithic, crust-forming lichens in subalpine habitats. The phylogenetic placement and the monophyly of Pleostigmataceae lack statistical support, but the family was resolved as sister to the order Verrucariales. This family comprises the species Pleostigma alpinum sp. nov., P. frigidum sp. nov., P. jungermannicola, and P. lichenophilum sp. nov. The placement of the genus Melanina is supported as a lineage within the Chaetothyriales. To date, this genus comprises the single species M. gunde-cimermaniae sp. nov. and forms a sister group to a large lineage including Herpotrichiellaceae, Chaetothyriaceae, Cyphellophoraceae, and Trichomeriaceae. The new phylogenetic analysis of the subclass Chaetothyiomycetidae provides new insight into genus and family level delimitation and classification of this ecologically diverse group of fungi.

scholarly journals TreeMerge: a new method for improving the scalability of species tree estimation methods

2019 ◽  
Vol 35 (14) ◽  
pp. i417-i426 ◽  
Author(s):  
Erin K Molloy ◽  
Tandy Warnow
Keyword(s):  
Large Scale ◽  
Species Tree ◽  
New Method ◽  
Divide And Conquer ◽  
Supplementary Information ◽  
Estimation Methods ◽  
Running Time ◽  
Tree Estimation ◽  
Computationally Intensive ◽  
A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Rapid Classification of Clostridioides difficile Strains Using MALDI-TOF MS Peak-Based Assay in Comparison with PCR-Ribotyping

2021 ◽  
Vol 9 (3) ◽  
pp. 661
Author(s):  
Adriana Calderaro ◽  
Mirko Buttrini ◽  
Monica Martinelli ◽  
Benedetta Farina ◽  
Tiziano Moro ◽  
...  
Keyword(s):  
Ionization Time ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Clostridioides Difficile ◽  
Pcr Ribotyping ◽  
Typing Methods ◽  
Set Up ◽  
Tof Ms

Typing methods are needed for epidemiological tracking of new emerging and hypervirulent strains because of the growing incidence, severity and mortality of Clostridioides difficile infections (CDI). The aim of this study was the evaluation of a typing Matrix-Assisted Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS (T-MALDI)) method for the rapid classification of the circulating C. difficile strains in comparison with polymerase chain reaction (PCR)-ribotyping results. Among 95 C. difficile strains, 10 ribotypes (PR1–PR10) were identified by PCR-ribotyping. In particular, 93.7% of the isolates (89/95) were grouped in five ribotypes (PR1–PR5). For T-MALDI, two classifying algorithm models (CAM) were tested: the first CAM involved all 10 ribotypes whereas the second one only the PR1–PR5 ribotypes. Better performance was obtained using the second CAM: recognition capability of 100%, cross-validation of 96.6% and agreement of 98.4% (60 correctly typed strains, limited to PR1–PR5 classification, out of 61 examined strains) with PCR-ribotyping results. T-MALDI seems to represent an alternative to PCR-ribotyping in terms of reproducibility, set up time and costs, as well as a useful tool in epidemiological investigation for the detection of C. difficile clusters (either among CAM included ribotypes or out-of-CAM ribotypes) involved in outbreaks.

scholarly journals Marine Network Protocols and Security Risks

2021 ◽  
Vol 1 (2) ◽  
pp. 239-251
Author(s):  
Ky Tran ◽  
Sid Keene ◽  
Erik Fretheim ◽  
Michail Tsikerdekis
Keyword(s):  
Network Protocols ◽  
Network Protocol ◽  
Identification System ◽  
Automated Identification ◽  
Security Risks ◽  
Domain Specific ◽  
Protocol Security ◽  
Challenges And Opportunities

Marine network protocols are domain-specific network protocols that aim to incorporate particular features within the specialized marine context that devices are implemented in. Devices implemented in such vessels involve critical equipment; however, limited research exists for marine network protocol security. In this paper, we provide an analysis of several marine network protocols used in today’s vessels and provide a classification of attack risks. Several protocols involve known security limitations, such as Automated Identification System (AIS) and National Marine Electronic Association (NMEA) 0183, while newer protocols, such as OneNet provide more security hardiness. We further identify several challenges and opportunities for future implementations of such protocols.

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