Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota.

BACKGROUND: Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models. RESULTS: As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra. CONCLUSIONS: Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.

Improving Species Level-taxonomic Assignment from 16S rRNA Sequencing Technologies.

Analysis of the bacterial community from a 16S rRNA gene sequencing technologies requires comparing the reads to a reference database. The challenging task involved in annotation relies on the currently available tools and 16S rRNA databases: SILVA, Greengenes and RDP. A successful annotation depends on the quality of the database. For instance, Greengenes and RDP have not been updated since 2013 and 2016, respectively. In addition, the nature of 16S sequencing technologies (short reads) focuses mainly on the V3-V4 hypervariable region sequencing and hinders the species assignment, in contrast to whole shotgun metagenome sequencing. Here, we combine the results of three standard protocols for 16S rRNA amplicon annotation that utilize homology-based methods, and we propose a new re-annotation strategy to enlarge the percentage of amplicon sequence variants (ASV) classified up to the species level. Following the pattern (reference) method: DADA2 pipeline and SILVA v.138.1 reference database classification (Basic Protocol 1), our method maps the ASV sequences to custom nucleotide BLAST with the SILVA v.138.1 (Basic Protocol 2), and to the 16S database of Bacteria and Archaea of NCBI RefSeq Targeted Loci Project databases (Basic Protocol 3). This new re-annotation workflow was tested in 16S rRNA amplicon data from 156 human fecal samples. The proposed new strategy achieved an increase of nearly eight times the proportion of ASV classified at the species level in contrast to the reference method for the database used in the present research. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sample inference and taxonomic profiling through DADA2 algorithm. Basic Protocol 2: Custom BLASTN database creation and ASV taxonomical assignment. Basic Protocol 3: ASV taxonomical assignment using NCBI RefSeq Targeted Loci Project database. Basic Protocol 4: Definitive selection of lineages among the three methods.

Role of allogeneic hematopoietic cell transplant for relapsed/refractory aggressive B-cell lymphomas in the CART era.

Anti-CD19 chimeric antigen receptor T cells (CART) has rapidly been adopted as the standard third-line therapy to treat aggressive B-cell lymphomas (ABCL) after failure of second-line therapy despite the lack of direct comparisons with allogeneic hematopoietic cell transplantation (alloHCT)-based strategies. Using the Grupo Español de Trasplante y Terapia Celular (GETH-TC) registry, we selected patients with the following characteristics: CART or alloHCT performed between 2016 and 2021; ≥18 years old; ABCL diagnosis; ≥2 lines of therapy; and either anti-CD19 CART or alloHCT as therapy at relapse. The analysis included a total of 316 (CART = 215, alloHCT = 101) patients. Median follow-up was 15 and 36 months for the CART and alloHCT cohorts, respectively. In the multivariate analysis, CART was confirmed to be similar to alloHCT for the primary study endpoint (progression-free survival) (hazard ratio [HR] 0.92, CI95%:0.56-1.51, p = 0.75). Furthermore, when the analysis was limited to only patients with chemo-sensitive diseases (complete and partial response) at infusion (CART = 26, alloHCT=93), no differences were reported (progression-free survival at month +18: 65% versus 55%, p = 0.59). However, CART had lower non-relapse mortality (HR 0.34, 95% CI: 0.13-0.85, p = 0.02). Given the lower toxicity and similar survival outcomes, these results suggest the use of CART before alloHCT.