Yes, Saturdays are somewhat weird days for software updates, but if you’re doing weekend work anyway, why wait to push bug fixes to the community? A very minor bug-fix update to Metaxa2 was released today, bringing the software to version 2.2.3.
Two things have changed in this version, both related to the genome mode. 1) We fixed a file reading bug in the ‘genome’ mode of the software. This bug caused the last sequence in an input FASTA file not to be read unless there was a newline after it. Since the ‘genome’ mode is rarely used by most users, we suspect not a lot of users have been affected by this bug.
2) While we were at it, we changed the behavior of the ‘genome’ mode to mirror that of the ‘auto’ mode, as the strict genome mode dropped sequences shorter than 2500 bp. We considered this behavior counter-intuitive to what most users would want, and has now changed the ‘genome’ mode to behave the same as the ‘auto’ mode and not drop short sequences.
No other changes have been made in this version. The update can be found at the Metaxa2 software page.
A new version of ITSx is released today. This minor update contains two minor bug fixes and two small new features.
The first bug was that ITSx returned empty sequences in the FASTA file for no detections for large input files. This has now been fixed.
The second bug fix is a bit more fuzzy and involved some fine-tuning of how large input files are handled in ITSx to stabilise E-value and score cut-offs.
The two new features are:
- The possbility to put the temporary directory in a custom location using the
- ITSx now warns when the input file contains sequences with identical identifiers, which usually leads to sequences being dropped from the input file.
The new update brings ITSx to version 1.1.3. Thanks for the users who have spotted bugs and suggested new features! Happy barcoding everyone!
Today, we released a minor update to Metaxa2, bringing it to version 2.2.2. The new version includes some bug fixes related to the Metaxa2 Database Repository, as well as a new “–temp” option allowing the user to specify the location for the temporary files. No other changes have been made in this version.
The update can be found at the Metaxa2 software page.
Exactly two years after we released the Metaxa2 database builder, here’s the first update to the software. Unfortunately, it is just a boring bug fix, but the good part is that brings back compatibility with the new version of HMMER (3.3) released in November 2019 (as noted here). It seems like it is mainly the Database builder which has been impacted with by this incompatibility, but we recommend everyone to update.
We have tried to bug check this version as good as we can to make sure we did not break any features while introducing this new compatibility. We think that this version is bug free, but as we wanted to push this out quickly, please be more observant than usual to odd behaviour, and make sure to report any bugs!
The update can be downloaded here: https://microbiology.se/sw/Metaxa2_2.2.1.tar.gz
ITSx has been updated with some minor bug fixes (solving bugs that caused big problems for a small subset of users).
The first bug was that the no detections file generated in a previous file was not removed before it was written to (if it happened to have the same name in a subsequent run). This could cause weird errors where sequences which were not part of the input file were reported as not detected, and subsequently inconsistent counts for the number of missing sequences. This bug should now be fixed (although I have to admit that it is hard to test for this error in all possible scenarios).
The second bug was very serious for anyone who worked with ITS sequences from Chlorophyta. The ‘-t’ option did not accept ‘G’ (the code for Chlorophyta) as an option, while it did accept ‘green algae’ or ‘chlorophyta’. The Chlorophyta profiles were also included in the default ‘all’ profiles mode, and thus this error did not manifest itself for the vast majority of users. I am sorry for the mess this must have caused for the Chlorophyta researchers using ITSx and thank the users of the software for pointing this error out.
Sorry for these bug fixes taking so long! It has been a very unusual and stressful spring and summer, and I hope to be able to be more responsive in the future. The new update brings ITSx to version 1.1.2. No other changes except the two bug fixes have been made in this version.
I am happy to share the news that the paper describing out software tool Mumame is now out in its final form! (1) The paper got published today in the journal Metabarcoding and Metagenomics after being available as a preprint (2) since last autumn. This version has not changed a whole lot since the preprint, but it is more polished and better argued (thanks to a great review process). The software is virtually the same, but is not also available via Conda.
In the paper, we describe the Mumame software, which can be used to distinguish between wildtype and mutated sequences in shotgun metagenomic sequencing data and quantify their relative abundances. We further demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets (3-6), and find that the tool is useful but that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than is needed for most other applications of shotgun metagenomics. Since the preprint was published, Mumame has also found use in our recently published paper on selection for antibiotic resistance in a Croatian macrolide production wastewater treatment plant, unfortunately with inconclusive results (7). Mumame is freely available here.
I again want to stress the fantastic work that Shruthi Magesh did last year as a summer student at WID in the evaluation of this tool. As I have pointed out earlier, I did write the code for the software (with a lot of input from Viktor Jonsson), but Shruthi did the software testing and evaluations. Thanks and congratulations Shruthi, and good luck in pursuing your PhD program!
- Magesh S, Jonsson V, Bengtsson-Palme J: Mumame: A software tool for quantifying gene-specific point-mutations in shotgun metagenomic data. Metabarcoding and Metagenomics, 3: 59–67 (2019). doi: 10.3897/mbmg.3.36236
- Magesh S, Jonsson V, Bengtsson-Palme J: Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572
- Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, 5, 648 (2014). doi: 10.3389/fmicb.2014.00648
- Lundström S, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103
- Pal C, Bengtsson-Palme J, Kristiansson E, Larsson DGJ: The structure and diversity of human, animal and environmental resistomes. Microbiome, 4, 54 (2016). doi: 10.1186/s40168-016-0199-5
- Kraupner N, Ebmeyer S, Bengtsson-Palme J, Fick J, Kristiansson E, Flach C-F, Larsson DGJ: Selective concentration for ciprofloxacin in Escherichia coli grown in complex aquatic bacterial biofilms. Environment International, 116, 255–268 (2018). doi: 10.1016/j.envint.2018.04.029
- Bengtsson-Palme J, Milakovic M, Švecová H, Ganjto M, Jonsson V, Grabic R, Udiković Kolić N: Pharmaceutical wastewater treatment plant enriches resistance genes and alter the structure of microbial communities. Water Research, 162, 437-445 (2019). doi: 10.1016/j.watres.2019.06.073
I just uploaded a mini update to ITSx, fixing a bug that caused the
--truncate option not to be accepted by the software in ITSx 1.1. This bug fix brings the software to version 1.1.1. No other changes have been introduced in this version. Download the update here. Happy barcoding!
A few days ago, my attention was turned to a duplicate in the COI database bundled with Metaxa2 2.2. While this duplicate sequence should not cause any troubles for Metaxa2 itself, it has created issues for people using the database itself together with, e.g., QIIME. Therefore, I have today issued a very very minor update to the Metaxa2 2.2 package as well as the entry in the Metaxa2 Database Repository, removing the duplicate sequence. I deemed that this was not significant enough to issue a new version, particularly as no code was changed and it did not cause issues for the software itself, so the version will stay at 2.2 for the time being. Happy barcoding!
Let me get straight to something somewhat besides the point here: summer students can achieve amazing things! One such student I had the pleasure to work with this summer is Shruthi Magesh, and a preprint based on work she did with me at the Wisconsin Institute for Discovery this summer just got published on bioRxiv (1). The preprint describes a software tool called Mumame, which uses database information on mutations in DNA or protein sequences to search metagenomic datasets and quantifies the relative proportion of resistance mutations over wild type sequences.
In the preprint (1), we first of all show that Mumame works on amplicon data where we already knew the true outcome (2). Second, we show that we can detect differences in mutation frequencies in controlled experiments (2,3). Lastly, we use the tool to gain some further information about resistance patterns in sediments from polluted environments in India (4,5). Together these analyses show that one of the most central aspects for Mumame to be able to find mutations is having a very high number of sequenced reads in all libraries (preferably more than 50 million per library), because these mutations are generally rare – even in polluted environments and microcosms exposed to antibiotics. We expect Mumame to be a useful addition to metagenomic studies of e.g. antibiotic resistance, and to increase the detail by which metagenomes can be screened for phenotypically important differences.
While I did write the code for the software (with a lot of input from Viktor Jonsson, who also is a coauthor on the preprint, on the statistical analysis), Shruthi did the software testing and evaluations, and the paper would not have been possible hadn’t she wanted a bioinformatic summer project related to metagenomics, aside from her laboratory work. The resulting preprint is available from bioRxiv and the Mumame software is freely available from this site.
- Magesh S, Jonsson V, Bengtsson-Palme J: Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572 [Link]
- Kraupner N, Ebmeyer S, Bengtsson-Palme J, Fick J, Kristiansson E, Flach C-F, Larsson DGJ: Selective concentration for ciprofloxacin in Escherichia coli grown in complex aquatic bacterial biofilms. Environment International, 116, 255–268 (2018). doi: 10.1016/j.envint.2018.04.029 [Paper link]
- Lundström S, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103 [Paper link]
- Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, 5, 648 (2014). doi: 10.3389/fmicb.2014.00648 [Paper link]
- Kristiansson E, Fick J, Janzon A, Grabic R, Rutgersson C, Weijdegård B, Söderström H, Larsson DGJ: Pyrosequencing of antibiotic-contaminated river sediments reveals high levels of resistance and gene transfer elements. PLoS ONE, Volume 6, e17038 (2011). doi:10.1371/journal.pone.0017038.
A few days ago I posted about that Bioinformatics had published our paper on the Metaxa2 Database Builder (1). Today, I am happy to report that PeerJ has published the first paper in which the database builder is used to create a new Metaxa2 (2) database! My colleagues at Ohio State University has used the software to build a database for the COI gene (3), which is commonly used in arthropod barcoding. The used region was extracted from COI sequences from arthropod whole mitochondrion genomes, and employed to create a database containing sequences from all major arthropod clades, including all insect orders, all arthropod classes and the Onychophora, Tardigrada and Mollusca outgroups.
Similar to what we did in our evaluation of taxonomic classifiers used on non-rRNA barcoding regions (4), we performed a cross-validation analysis to characterize the relationship between the Metaxa2 reliability score, an estimate of classification confidence, and classification error probability. We used this analysis to select a reliability score threshold which minimized error. We then estimated classification sensitivity, false discovery rate and overclassification, the propensity to classify sequences from taxa not represented in the reference database.
Since the database builder was still in its early inception stages when we started doing this work, the software itself saw several improvements because of this project. We believe that our work on the COI database, as well as on the recently released database builder software, will help researchers in designing and evaluating classification databases for metabarcoding on arthropods and beyond. The database is included in the new Metaxa2 2.2 release, and is also downloadable from the Metaxa2 Database Repository (1). The open access paper can be found here.
- Bengtsson-Palme J, Richardson RT, Meola M, Wurzbacher C, Tremblay ED, Thorell K, Kanger K, Eriksson KM, Bilodeau GJ, Johnson RM, Hartmann M, Nilsson RH: Metaxa2 Database Builder: Enabling taxonomic identification from metagenomic and metabarcoding data using any genetic marker. Bioinformatics, advance article (2018). doi: 10.1093/bioinformatics/bty482
- Bengtsson-Palme J, Hartmann M, Eriksson KM, Pal C, Thorell K, Larsson DGJ, Nilsson RH: Metaxa2: Improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15, 6, 1403–1414 (2015). doi: 10.1111/1755-0998.12399
- Richardson RT, Bengtsson-Palme J, Gardiner MM, Johnson RM: A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data. PeerJ, 6, e5126 (2018). doi: 10.7717/peerj.5126
- Richardson RT, Bengtsson-Palme J, Johnson RM: Evaluating and Optimizing the Performance of Software Commonly Used for the Taxonomic Classification of DNA Sequence Data. Molecular Ecology Resources, 17, 4, 760–769 (2017). doi: 10.1111/1755-0998.12628