Pooling data in metagenome assembly
With metagenomes, there's several strategies and no one-size-fits-all. 
 You can spend a lot of time playing with the data to try to get the "best assembly."  But it depends on what you're trying to do, e.g. whether or not you are mostly interested in the highest abundant species or are interested in the less abundant ones too.  

But to propose a strategy that seems reasonable and hasn't been mentioned yet, my initial thoughts are that since the gut microbiome isn't complex, you can likely get decent assemblies from each run separately.  Then you can run a contig clustering algorithm (e.g. MetaBAT) to bin the contigs into genomes.  Next compare the bins from the various assemblies (i.e. cluster the clusters).  

It may or may not be worth the trouble to try to combine the related bins' contigs into a consensus (pan)genome sequence.  If you want to, methods that have been used successfully include shredding the contigs into overlapping chunks and assembling with an OLC assembler.  But if you're interested in KO:read-counts (for example), a consensus genome sequence isn't really required.  Cross-mapping the unassembled reads can be useful too (i.e. a sample may have a low-abundance OTU that doesn't produce good contigs, but it can be associated with an OTU that is better assembled in another sample).

If you provide more detail on your goal, I can comment further.