Search bioRxiv⌕ Search

Biology subjects

Bastida, F.

Publications and source records attributed to Bastida, F..

2 recordsLinked to original sources

A comparison among EL-FAME, PLFA, and quantitative PCR methods to detect changes in the abundance of soil bacteria and fungi

EL-FAME (ester-linked fatty acid methyl ester), PLFA (phospholipid fatty acid) and qPCR (quantitative PCR) of ribosomal genes are three of the most common methods used to quantify soil microbial communities. The reliability of these three methods has not been simultaneously compared in situations of rapid changes in soil microbial abundances. For this purpose, we (i) incubated badland, cropland, and forest soils with nutrients or antibiotics for 2, 7, 14, and 28 days, (ii) quantified total, bacterial, and fungal abundances through EL-FAME, PLFA, and qPCR methods, and (iii) measured soil basal respiration. The general dynamic patterns of the three soil microbial fractions in response to soil addition of nutrients and antibiotics were captured by the three methods, which led to strong and positive associations between the abundances of total microorganisms, bacteria, and fungi measured by the three techniques. However, these relationships were found to be stronger between the EL-FAME and PLFA results, indicating that reliability of the fatty-acid based methods is higher than that of the qPCR. Further, soil basal respiration was associated to a higher extent with total, bacterial, and fungal abundances captured by EL-FAME and PLFA analyses than with those measured by qPCR, which suggests that the first two methods are most closely related to the soil living microbial community. In general, dynamics in the abundance of total and bacterial communities were better captured than those of fungi. The PLFA analysis seems to perform better than the EL-FAME method in forest soil and in detecting the small antibiotic-induced decreases in microbial abundances. Since the EL-FAME method is cheaper and allows a much faster processing of samples than the PLFA method, and the reliability of both methods is similar in detecting rapid changes of soil microbial abundances, choosing EL-FAME over PLFA may be advantageous in most cases.

microbiology↗

Database-independent analysis of probable post-translational modifications of soil proteins across ecosystems

The identification rate of measured peptide spectra to proteins barely scratches 1% in best-case scenarios. Hundreds of thousands of valuable spectra are lost as no viable match in the database is found. Here, we apply the delta m/z plot that was previously implemented in MSnbase as tool for quality control to 63 soil samples from three ecosystems with different vegetation (39 forests, 11 grasslands, and 13 shrublands) with the aim to extract probable post-translational modifications (PTM) without the need of a reference database. The validity of the approach was verified with amino acids proposed for their respective 1 Da mass interval and compared to their relative abundance in proteins. We found that the average probable PTM and most known PTMs proposed for the mass intervals are similar across ecosystems. Otherwise, 11 mass intervals changed significantly in relative abundance in the three ecosystems but only for one an annotation could be proposed. Our approach not only highlights the opportunity of the database-independent analysis in soil metaproteomics but paves the way for targeted analysis of the yet unknown PTMs.

ecology↗