16S species-level taxonomic assignment--what is the current state of the art? We currently use DADA2 for picking ASVs and the assignTaxonomy funciton for assingment to genera. Google does bring up various recent articles on species-level assignment with 16S. 

Does anyone have an opinion on the current best-practice?

More simply, are there any current candidates for reasonably accurate species-level assignment?
I have been using dada2 and phyloseq (phangorn for trees) combination to analyze a V4 region 16s rRNA data set. I find their approach and explanations very understandable and usable since I prefer R.
I was under the impression that even full-length 16s rRNA gene sequences were inadequate to classify up to species level since closely related species within a genus can have identical 16S rRNA gene sequences.
But, turns out, intra-genomic variants of this gene within a species or even strain may allow their unambiguous identification according to this paper:
Johnson, J.S., Spakowicz, D.J., Hong, B. et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun 10, 5029 (2019). https://doi.org/10.1038/s41467-019-13036-1) available at: https://rdcu.be/b5cgB
Another relevant article regarding using black box ML algorithms (random forests) versus a straightforward logistic regression is discussed in this one:
Topçuoğlu BD, Lesniak NA, Ruffin MT 4th, Wiens J, Schloss PD. A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems. mBio. 2020;11(3):e00434-20. Published 2020 Jun 9. doi:10.1128/mBio.00434-20
Since the OP has probably already moved on long since the original query, I am writing this to document relevant current references for myself and anyone researching this topic on StackExchange Bioinformatics.