software recommendation for metagenome assembly for low abundance bacteria

[hugomarquez]

I hope to obtain some MAGs for certain bacteria from my samples. We know they do exit in the samples by 16S amplicon, but the abundance is low. Is there any recommendation about how to assembly the MAGs for these bacteria? For instance, what software to use for binning (metabat2, maxbin2, or others), and if consensus best-quality bins shall be generated. Thank you!

[GenomicSeq]

Hello hugomarquez some tools I've been familiar with are MetaBAT2, MaxBin2, CONCOCT, and MyCC. I know there are also some more recent ones I'm forgetting about but I'll try to see if I have notes stored somewhere on them in my giant list of papers to read.

[konstantia_lynch]

Hello Hugo, I have been thinking about this matter a lot and have come up with the following idea. Let's assume we have several metagenomes representing a specific area. We expect that all our low-abundance taxa of interest are uniformly distributed across the area, along with their corresponding DNA and reads.

The first step is to assemble contigs, for which we could use a tool like Metaspades. From there, we can individually construct MAGs from each sample. It is preferable to use three or four binners, such as Concoct, Metabat, and Maxbin. We can then use DAStool to obtain consensus bins from the results of all three or more software.

Now that we have MAGs constructed from the most abundant and less diverse DNA in the samples, the next step is to combine all the raw metagenomic datasets (into one file) and merge all the constructed MAGs (into another file). The combined-MAGs file can be used to build an indexed database, for example, using Bowtie2. We can then map the combined raw metagenomic reads onto this database, saving into single object only the reads that were not utilized for contigs and bins assembly. Since this object contains all the DNA from the initial samples, but not the DNA of the most abundant taxa, we expect that the quantity of reads belonging to low-abundance taxa would be sufficient to assemble contigs and cluster them into bins.

Therefore, the next step is to use an assembler and a binner on this dataset enriched with less abundant DNA. The hypothesis is that this will result in more or less complete MAGs of rare microbes. Hooray!

It is not necessary to map raw reads onto abundant MAGs. We can also utilize initial contigs to obtain the reads that were not included in the MAGs. However, in this case, more data would be lost, as some portion of contigs had already been discarded by the binning program before MAGs were constructed. Therefore, using contigs instead of MAGs would leave us with only the reads that were not used by either the assembler or the binner.

I hope this clarifies the approach I have in mind. Please let me know your thoughts on that. It also would be great if anybody else would comment such strategy, as I am not a deeply experienced person in such things.

Best regards,
Konstantin.