0 1.0 Sulfur metabolism               Sulfate adenylyltransferase (ATP) cysN 1 54 33 0.000 1.6 0.6 Adenylyl-sulfate kinase Obeticholic Acid mw aspK 1 52 15 0.000 3.2 0.3 Phosphoadenylyl-sulfate reductase cysH 1 26 22 ns 1.1 0.9 Adenylyl-sulfate reductase

aprA 1 15 10 ns 1.4 0.7 3′(2′),5′-bisphosphate nucleotidase cysQ 1 67 40 0.000 1.6 0.6 Hydrogensulfite reductase dsrA 1 13 15 ns 0.8 1.3 Sulfite reductase (NADPH) cysJ 1 28 4 0.000 7.6 0.1 Sulfite reductase (DSR) dsrB 1 13 14 ns 1.0 1.0 Sulfite reductase (ferredoxin) sir 1 22 6 0.000 3.7 0.3 Cysteine synthase cysK 1 >100 >100 ns 1.0 1.0 Thiosulfate oxidise soxB 1 66 7 0.000 9.1 0.1 Nitrogen metabolism               Ammonia monooxygenase amoA 1 8 29 0.000 0.3 3.6 Nitrate reductase napA 1 2 13 0.000 0.1 8.0 Nitrate reductase narG 1 17 28 0.000 0.6 1.7 Nitrate reductase nasA 1 68 34 0.000 2.0 0.5 Nitric oxide reductase norB 1 2 23 0.001 0.1 9.4 Nitric oxide reductase qnor 1 22 23 ns 1.0 1.0 Nitrite reductase nirK 1 17 3 0.000 5.2 0.2

Nitrite reductase nirS 1 2 30 0.000 0.1 16.4 Nitrous oxide reductase nosZ 1 10 35 0.030 0.3 3.6 Nitrite reductase nirB 1 64 44 0.000 RO4929097 in vivo 1.4 0.7 Nitrite reductase nirA 1 7 1 0.018 5.6 0.2 Nitrite reductase nrfA 1 1 45 0.000 0.0 58.4 Nitrogenase (molybdenum-iron) nifD 1 1 23 0.000 0.0 24.6 Nitrogenase (iron) nifH 1 15 23 0.006 0.6 1.6 *Indicate components that are significantly different between the two samples (q < 0.05)

based on the Fisher’s exact test using corrected q-values (Storey’s FDR multiple test correction approach). ‡Housekeeping genes: gyrA, gyrB, recA, rpoA and rpoB. †Direct comparison between the frequency of different functional genes, either within or between metagenomes, was not established since length and copy number of the gene was not incorporated in the formula. TP: top pipe. BP: bottom pipe. NS: not significant. ND: not determine. The wide range of annotated functions associated in several sulfur pathways may be indicative of the availability 3-mercaptopyruvate sulfurtransferase of several electron donors at wastewater pipes undergoing corrosion. While the role of some bacterial groups might be predicted based on previous studies, our study suggests that additional bacterial groups might be playing important roles within wastewater concrete corrosion processes. This is the case for SRB as they are a phylogenetically diverse group that cannot be monitored using a single 16S rRNA gene assay ( Additional file 1, Figure S7). Our approach provides a sequence-based framework that can be used to monitor relevant microbial populations via function-specific assays. These assays can be used to measure the expression of key genes involved in corrosion processes, and hence be used to provide a condition assessment tool prior to corrosion processes that are irreversible.