Poly A selection is quite common, but OP didn't mention his protocol. Also, poly-A selection biases your samples away from other human RNA species that don't have the tail. You don't need any special protocol for bacterial RNA-seq if you're working in an RNAse free environment. Therefore, bacterial sequences are (anecdotally) quite common in human samples that haven't been processed with care, or are taken from tissues with microbiota. OP is asking for a recommendation for an aligner for bacterial samples that doesn't concern itself with splicing (you can imagine the algorithmic mistakes a splice-aware aligner can make in the densely packed bacterial genomes). Aligning against bacterial genomes is a good quality control routine, especially when considering the prevalence of laboratory contaminants such as Mycoplasma.
From my experience, even with several rounds of DNAse treatment, if you are sequencing deeply, a residual noise in the genome can be observed that can be explained as either spurious transcription or DNA contamination that evades multiple DNAse rounds. This has been described in the following papers.
https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-13-734
http://mbio.asm.org/content/3/4/e00156-12.short
http://jb.asm.org/content/197/1/18.short
http://advances.sciencemag.org/content/2/3/e1501363.abstract
I'm guessing this is why you were downvoted for the 'quick-to-dismiss' fairly common sample contaminants including bacterial sequences and even DNA sequences.
Do you already know the particular bacteria that you want to align against, or are you still trying to determine that? For what it's worth, bacteria tend to not have splicing, so you can often get away with directly using bowtie2/bwa/etc.
Yes, i am using streptococcus pneumonia ATCC700669 (FM211187). I downloaded the fasta file.. made the index file by bowtie-build and then mapped using tophat2. The result that i got for the diseased sample is :
And for the healthy (was just exoerimenting with the healthy sample, what comes out)
By just looking at the result, do you say that the bacterial genome remain are into the sample???
Our internal threshold for calling a sample contaminated is 0.5% unique alignments, so I guess the diseased sample is borderline. I don't know where the samples were sourced from, so you might not expect a high amount of the bugs in the samples, even if the patient had them.
I just saw this paper mentioned on twitter (it literally just came out). It and some of the references therein may be of interest to you. That particular paper is for one of the iobio tools, which are always really slick.
you could use SNAP/Bowtie2 to align the reads against bacterial genomes from NCBI. There are pipelines built for this, but it would be tedious if your main goal is not to identify the pathogens in the data.
http://chiulab.ucsf.edu/surpi/