Influence of agricultural activities in the structure and metabolic functionality of paramo soil samples in Colombia studied using a metagenomics analysis in dynamic state

Bacterial diversity in high Andean grassland soils disturbed with Lepidium meyenii crops evaluated by metagenomics

Soil quality is usually determined by its physical-chemical characteristics without taking into account the bacterial communities that play a fundamental role in the chemical decomposition of plant nutrients. In this context, the objective of the study was to evaluate bacterial diversity in high Andean grassland soils disturbed with Lepidium meyenii cultivation under different gradients of use (first, second and third use) and crop development (pre-sowing, hypocotyl development and post-harvest). The sampling was carried out in the Bombón plateau in the central Andes of Peru, during the rainy and low water seasons, by the systematic method based on a specific pattern assigned in a geometric rectangular shape at a depth of 0 - 20 cm. The characterization of the bacterial communities was carried out through the metagenomic sequencing of the 16S rRNA. 376 families of bacteria were reported, of which it was determined that there was a significant change in bacterial composition and distribution in relation to use pressure. There were no major changes due to the development of Lepidium meyenii. The families most sensitive to use pressure and soil poverty indicators were Verrucomicrobiaceae, Acidobacteraceae and Aakkermansiaceae.

Soil Microfungi of the Colombian Natural Regions

Although Colombia was one of the first tropical countries where an effort was made to gather mycological flora, contributions to the taxonomy, diversity, and ecology of soil microfungi are still scarce. In this study, the diversity of soil microfungi was studied collecting data from literature according to the Colombian natural regions: Andean, Amazonian, Caribbean, Orinoquía, Pacific, and Insular. The majority of the records comes from the Andean region, the most accessible to research. The other regions have been much less studied, with the Insular one with no data at all. International literature reported, up to now, ca. 300 different species of soil microfungi belonging to 126 different genera and 6 phyla (Ascomycota, Basidiomycota Mucoromycota, Glomeromycota, Mortierellomycota, and Olpidiomycota). Vescicular-Arbuscular fungi were widely investigated with Acaulospora and Glomus, the most recorded genera with ca. 20 species each. Ascomycota was the most diverse phylum with Penicillium, Aspergillus, and Fusarium representing the majority. Mortierella is strongly present in Mortierellomycota, and in the panorama of all recorded fungi, too. The other phyla and genera were less recorded. It is, therefore, evident the need to continue studying the soil microfungi in Colombia to have a better understanding of soil functioning and its ecosystem services.

Indicators for assessment of soil quality: a mini-review

Soil quality is the competence of soil to perform necessary functions that are able to maintain animal and plant productivity of the soil. Soil consists of various physical, chemical, and biological parameters, and all these parameters are involved in the critical functioning of soil. There is a need for continuous assessment of soil quality as soil is a complex and dynamic constituent of Earth's biosphere that is continuously changing by natural and anthropogenic disturbances. Any perturbations in the soil cause disturbances in the physical (soil texture, bulk density, etc.), chemical (pH, salinity, organic carbon, etc.), and biological (microbes and enzymes) parameters. These physical, chemical, and biological parameters can serve as indicators for soil quality assessment. However, soil quality assessment cannot be possible by evaluating only one parameter out of physical, chemical, or biological. So, there is an emergent need to establish a minimum dataset (MDS) which shall include physical, chemical, and biological parameters to assess the quality of the given soil. This review attempts to describe various physical, chemical, and biological parameters, combinations of which can be used in the establishment of MDS.

A meta-barcoding analysis of soil mycobiota of the upper Andean Colombian agro-environment

Colombia is a country for which one of the highest biodiversity rates is reported, and one of the first in the tropical areas where an effort was made to gather information on indigenous fungi. Nevertheless, mycological data are still scarce and discontinuous, above all on soil fungi. The present study wanted to contribute to unveil the large soil fungal biodiversity in the upper Andean Colombian agro-ecosystems. The studied area is located in the department of Boyacà, considered with a notable economical value, partly devoted to subsistence agriculture. More than 150 described species were revealed in this study, belonging to 5 phyla with Ascomycota representing the dominant taxon. Basidiomycota and Zygomycota are also well represented, dominated by species of the genus Sebacina and Mortierella respectively, mainly distributed in the semi-natural plots (woodland and grassland). Most of the species are reported as first records for Colombia. Some of them are particularly interesting for their conservation significance such as Geoglossum fallax, which is the dominant species in the unimproved grassland plot. The bootstrap-based clustering analysis showed a different distribution of the species in orchards and non-cultivated areas as a possible response of the fungal community to different use of soil in the agro-environment.

Clostridium butyricum population balance model: Predicting dynamic metabolic flux distributions using an objective function related to extracellular glycerol content

BACKGROUND

Extensive experimentation has been conducted to increment 1,3-propanediol (PDO) production using Clostridium butyricum cultures in glycerol, but computational predictions are limited. Previously, we reconstructed the genome-scale metabolic (GSM) model iCbu641, the first such model of a PDO-producing Clostridium strain, which was validated at steady state using flux balance analysis (FBA). However, the prediction ability of FBA is limited for batch and fed-batch cultures, which are the most often employed industrial processes.

RESULTS

We used the iCbu641 GSM model to develop a dynamic flux balance analysis (DFBA) approach to predict the PDO production of the Colombian strain Clostridium sp IBUN 158B. First, we compared the predictions of the dynamic optimization approach (DOA), static optimization approach (SOA), and direct approach (DA). We found no differences between approaches, but the DOA simulation duration was nearly 5000 times that of the SOA and DA simulations. Experimental results at glycerol limitation and glycerol excess allowed for validating dynamic predictions of growth, glycerol consumption, and PDO formation. These results indicated a 4.4% error in PDO prediction and therefore validated the previously proposed objective functions. We performed two global sensitivity analyses, finding that the kinetic input parameters of glycerol uptake flux had the most significant effect on PDO predictions. The other input parameters evaluated during global sensitivity analysis were biomass composition (precursors and macromolecules), death constants, and the kinetic parameters of acetic acid secretion flux. These last input parameters, all obtained from other Clostridium butyricum cultures, were used to develop a population balance model (PBM). Finally, we simulated fed-batch cultures, predicting a final PDO production near to 66 g/L, almost three times the PDO predicted in the best batch culture.

CONCLUSIONS

We developed and validated a dynamic approach to predict PDO production using the iCbu641 GSM model and the previously proposed objective functions. This validated approach was used to propose a population model and then an increment in predictions of PDO production through fed-batch cultures. Therefore, this dynamic model could predict different scenarios, including its integration into downstream processes to predict technical-economic feasibilities and reducing the time and costs associated with experimentation.