Fig. 2: Protein-to-RNA ratio distributions within a microbial community. | Nature Communications

Fig. 2: Protein-to-RNA ratio distributions within a microbial community.

From: Integration of absolute multi-omics reveals dynamic protein-to-RNA ratios and metabolic interplay within mixed-domain microbiomes

Fig. 2

a Comparison of the boxplot of protein-to-RNA ratios of selected MAGs reconstructed from the SEM1b community as well as those previously reported in the literature. (Bacteria: green, Archaea: red, Eukarya: blue). The boxes span the 25th–75th percentiles with the central bars being the medians. Whiskers extend maximum up to 1.5× the inter-quartile range or, if possible, until the most extreme of the data points. Points beyond the whiskers are considered outliers. The protein-to-RNA ratios for E. coli was retrieved from Taniguchi et al.2, Yeast1 from Ghaemmaghami et al.21, Yeast2 from Lu et al.22, Human1 from Schwanhausser et al.23 and Human2 from Li et al.24. The number of independent genes per organism used in the plot are as follows: E. coli = 1018, TISS1 = 587, CLOS1 = 783, RCLO1 = 799, TEPI1 = 433, COPR1 = 75, Yeast1 = 6238, Yeast2 = 6330, Human1 = 5028, Human2 = 5028, METH1 = 93. b The distribution of the Pearson correlation coefficients (PCC) between transcripts and their corresponding proteins computed across the time points. With a median PCC of 0.41, the change in the amount of a given transcript over time seemingly does not translate into a change in the amount of the corresponding protein. c. Per time-point scatterplots of the absolute protein and transcript levels for ORFs that produced both detectable transcript and protein in SEM1b data sets. For simplicity, only four representative MAGs are shown, with all MAGs depicted in Supplementary Fig. 2. d The plot shows how the linearity parameter k between RNA and protein changes over time for the different MAGs. The linearity represents how a change in RNA level is reflected in a change in the corresponding protein level. The third-grade polynomial fit allows up to two bends to the curve. The parameter ranges from 0 to 1, and increasingly smaller values translate in fewer proteins being expected for the same level of RNAs. The populations CLOS1, METH1, and TEPI1 are converging toward the same values, while RCLO1 has a parallel trend, which collectively suggests the existence, and the reaching of a metabolic equilibrium among them.

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