Transport Processes And Unit Operations Solution Manual

Further experimental advancements have boosted resolution of microbial community research, including procedures offering improved sensitivity to capture also low-abundant species [9], or an approach for allowing profiling novel microorganisms without being limited by gene/protein data available in reference sequences, in consequence significantly expanding the scope of metagenomics research [10]. Together, such technologies have popularized metagenomics techniques finding applications in diverse areas such as human health, nutrition, industrial production, or environment remediation [11].

At an industrial scale, bioleaching systems are used in recovery of metal ores (e.g. gold and silver) or to leach base metals such as copper, cobalt, nickel and zinc, as well as low-grade uranium ores. Extending the approach to non-base metals is not yet commercially attractive. The main reasons for the lack of commercial bioleaching operations are seen in efficiency constraints, costs associated with the construction of suitable bioreactors as well as in logistic issues related to vast volume of material to be processed [13]. Recently, mining companies are confronted with a set of drivers that affect the economics of mining. Among those is a growing global demand for raw metals as well as tightening environmental legislation. Efficiency gains can be expected through the adoption and/or optimization of bioleaching processes [17].

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Formal representation of a microbial community. Starting with a microbial community M composed of individual species mi and the set of protein coding genes G observables become apparent on the individual gene level (O1), on the pathway level for each species (O2), and on the level of inter-species molecular processes finally generating a community observable O3. Integrative analysis aims at deriving a model on the level of individual genes gi explaining an emergent property O3M

Pathway-centric bioleaching model. Pathway model for cooperation of At. ferrooxidans and At. thiooxidans in chalcopyrite bioleaching. Species-specific molecular processes pi (schematic subgraphs represent protein coding genes and interactions) assigned to the thiosulfate, the polysulfide and the iron oxidation pathway cooperate in mineral dissolution from chalcopyrite. Mechanisms deemed responsible for increased leaching efficiency in a co-culture setting at the interface with the mineral surface as indicated by arrows include (1) proton availability, (2) sulfur layer removal, (3) hindering jarosite formation

Expanding ortholog screening for the core COG category energy production and conversion (with in total 289 genes for At. ferrooxidans and 290 genes for At. thiooxidans) to all COG categories identifies five additional COG terms holding orthologs at varying degree (Fig. 4b), including secondary metabolite biosynthesis, inorganic ion transport, coenzyme transport, amino acid transport, and posttranslational modification. Ortholog assignment results in linking of specific transport-associated functionalities which may well add to the cooperative phenomenon as outlined in Fig. 3. Such additional categories hold further a number of species-specific genes, with in total 221 genes on the At. ferrooxidans side, and 151 genes for At. thiooxidans. For deciphering if members of this gene set prone to being involved in key aspects of chalcopyrite leaching processes as presented in Fig. 3 are already identified in the cooperation context or in the specific bioleaching utilization context keyword-base literature screening was performed, with results presented in Table 2.

Molecular model of cooperation. Ortholog molecular model on energy production and conversion together with selected transport categories. Nodes represent molecular units, with the node diameter scaling with the number of features included. Edges across units indicate significant dependencies of molecular features across units. Color-coding represents the number of interactions of At. ferrooxidans-specific genes linkable to ortholog genes embedded in units. Numbers in brackets below each node indicate genes assigned to energy production and conversion and number of genes assigned to transport categories (secondary metabolites biosynthesis, transport and catabolism; inorganic ion transport and metabolism; coenzyme transport and metabolism; amino acid transport and metabolism)

We consider the molecular units presented in Fig. 5 as individual molecular processes pi sharing genes across species boundaries, allowing us to postulate a mapping of O3M := f(pi). In the given analysis the ortholog model involving COG terms energy production and conversion together with specific transport terms is used as core structure, adding molecular functionality coming from At. ferrooxidans only (lack of At. thiooxidans-specific interaction data).

Utilizing species-specific pathway information allows deriving a first mechanistic model aimed at describing phenomena adding to improved bioleaching in the co-culture situation, essentially involving the thiosulfate, the polysulfide and the iron oxidation pathway. These constituents improve mineral dissolution from chalcopyrite via proton attack, sulfur layer removal, and hindrance of jarosite formation. Analyzing involved genes on the level of COG terms and ortholog mapping links the central term energy production and conversion with specific transport processes, namely secondary metabolites biosynthesis, transport and catabolism, inorganic ion transport and metabolism, coenzyme transport and metabolism, and amino acid transport and metabolism. This term set includes a number of non-ortholog genes from both species, a subset being already discussed in the context of microbial communities and bioleaching.

Certainly, a description at the level of COG terms does not allow delineation of integrated molecular processes. Building gene-centric interaction networks followed by segmentation according to topological criteria provides means for approximating such processes. Executing this procedure for the ortholog network of At. ferrooxidans and At. thiooxidans with focus on energy production and conversion coupled with identified transport terms results in a molecular process model bridging energy production and transport processes in shared molecular units. Integrated processes identified include iron oxidation, nitrogen metabolism and proton transport, segments covering sulfur oxidation and nitrogen metabolism, and a set of ion transporter functionalities. Including At. ferrooxidans-specific genes in this network results in a composite representation of shared community functionality and specific add-ons of one species. Of particular interest is Carbonic anhydrase, described as a constituent to the polysulfide pathway [56]. This gene has been found as associated with biofilm formation in a very recent proteomics study [57]. While the exact contributions of Carbonic anhydrase to a bioleaching process are unknown, three mechanisms can be conceived, including (i) positive impact on ammonia utilization of other consortia members by removal of environmental carbon disulfide (CS2) [58], (ii) enabling At. ferrooxidans to utilize CS2 as alternative energy source and (iii) contributing to inorganic carbon fixation [59]. A second gene, Homocitrate synthase, is described as an essential component of lysine biosynthesis and has been found upregulated in a screen searching for quorum-sensing-related molecules [60], suggesting a role in cell-density-dependent processes implicated in the formation of biofilms.

The approach presented in this work allows deriving hypotheses on coupled molecular processes, providing an alternative perspective of synergistic effects and community-based emergent properties. With the concept of dynamical hierarchies established, availability of annotation and interaction information in the public domain, and open source libraries for computing networks and segments this approach is of general applicability. A major present pitfall is consolidated availability of molecular data needed to populate the data structures. Necessary gene annotation is distributed across numerous individual sources, hampering integration for given annotation beyond the challenge of adding annotation to novel species identified in metagenomics. Utilizing orthology for annotation imputation naturally results in biases, becoming even more pronounced when going to a larger set of species composing the community. Of equal relevance, and with even less coverage presents interaction information, being either generic on a pathway level, or only covering selected species. For fully leveraging on the power of integrative, network-based analysis procedures realizing common grounds on annotation and interaction information represents a major challenge ahead in the field, partly addressed by hybrid approaches in approximating interactions as done with STRING.

Increasing aquifers' recharge and storage is of great importance in addressing challenges posed by climate change and growing water demand. Managed Aquifer Recharge (MAR) technologies may ensure water supply for agriculture and diminish impacts from groundwater overexploitation. The expansion of MAR solutions in Europe still requires the implementation of these waterworks at their maximum efficiency. Physical clogging is one of the main bottlenecks for these technologies. In spreading methods, during water recharge, eroded clays from surface runoff reach the infiltrating surface and intrude into the soil matrix, decreasing the basin infiltration capacity over time. The resulting loss in performance increases the operation and maintenance (O&M) costs and, in extreme cases, can lead to the MAR site's abandonment. Thus, it is vital to assess the risk of physical clogging during the MAR planning phase, extending the MAR scheme lifespan and minimising O&M costs. Our study aims to develop a comprehensive model for physical clogging transferable to multiple MAR sites, based on the characterisation of the sediment matrix and MAR operations. To achieve this, we built a semi-empirical 1D numerical model for physical clogging. Evolution in soil permeability via the Kozeny-Carman equation is computed in function of depth based on the input of fines into the soil matrix and the porous media characteristics. The vertical distribution of fines is derived through a general relationship from a systematic review of multiple studies in the literature. The model allows computing the evolution in infiltration rates over time for the MAR site and the depth of soil to be treated to restore infiltration efficiency. Preliminary validation at the field scale is conducted at a MAR infiltration basin in Suvereto, Italy. To spatially apply the model, zoning is performed through an electromagnetic induction (EMI) survey, defining areas with similar soil properties. Values of hydraulic conductivity near saturation and soil samples were collected to characterise the sediment matrix and fines content for the entire basin. Predictions of the expected decrease in infiltration capacity for spreading methods assists maintenance scheduling and reduce O&M costs for the specific site. The proposed model for physical clogging can serve as a tool for decision support when exploring a set of design alternatives prior to MAR construction. be457b7860