Sludge digestibility and functionally active microorganisms in methanogenic sludge digesters revealed by E. coli-fed digestion and microbial source tracking.

Methanogenic sludge digestion plays a pivotal role in attenuating and hygienizing the massively-produced waste activated sludge (WAS), which is predominantly composed of microbial cells and extracellular polymeric substances (EPS). The efficient sludge digestion requires a variety of functionally active microorganisms working together closely to convert sludge organic matter into biogas. Nonetheless, the digestion efficiency (or digestibility quantified as carbon removal efficiency) of major sludge constituents (i.e., microbial cells and EPS) and associated functionally active microorganisms in sludge digesters remain elusive. In this study, we identified the digestibility of sludge microbial cells and the associated functionally active microorganisms by using Escherichia coli (E. coli)-fed digestion and microbial source tracking. The average carbon removals in four digesters fed with fresh WAS (WAS-AD), thermal pretreated WAS (Thermal-WAS-AD), E. coli cells (E.coli-AD) and thermal pretreated E. coli cells (Thermal-E.coli-AD) were 30.6 ± 3.4%, 45.8 ± 2.9%, 69.0 ± 3.4% and 68.9 ± 4.6%, respectively. Compared to WAS-AD and Thermal-WAS-AD, the significantly higher carbon removals in E. coli-AD and Thermal-E. coli-AD suggested the remarkably higher digestibility of microbial cells than EPS, and releasing organic matter from EPS might be a rate-limiting step in sludge digestion. Functionally active microorganisms for microbial cell digestion predominantly included fermenters (e.g., Petrimonas and Lentimicrobium), syntrophic acetogens (e.g., Synergistaceae) and methanogens (e.g., Methanosaeta and Methanosarcina). Microbial source tracking estimation showed that the microbial cell-digesting populations accounted for 35.6 ± 9.1% and 70.3 ± 10.1% of total microbial communities in the WAS-AD and Thermal-WAS-AD, respectively. Accordingly, the functionally active microorganisms for digestion of both microbial cells and EPS accounted for 64.5 ± 12.1% and 97.3 ± 2.0% of total digestion sludge microbiome in WAS-AD and Thermal-WAS-AD, respectively. By contrast, feeding WAS-derived microorganisms accounted for 23.2 ± 4.4% and 2.3 ± 1.2% of total microbial communities in the WAS-AD and Thermal-WAS-AD, respectively.

Development of an alkaline/acid pre-treatment and anaerobic digestion (APAD) process for methane generation from waste activated sludge.

Anaerobic sludge digesters are biorefineries for energy recovery from waste activated sludge (WAS) via methane production, in which disintegration of floc structure and microbial cells is a major challenge in releasing extracellular polymeric substances (EPS) and cytoplasmic macromolecules for subsequent hydrolysis and fermentation. Here, we developed a new process combining alkaline/acid pre-treatments and anaerobic digestion (APAD) to improve sludge digestion. Both alkaline and acid pre-treatments effectively disintegrated the floc structure and microbial cells to release sludge organic contents. Under the optimized alkaline/acid pre-treatment condition, carbon removal achieved 52.8 ± 1.7% in APAD digesters, in contrast to 30.9 ± 2.2% and 42.4 ± 1.6% in anaerobic digesters fed with fresh WAS (control-AD) and thermal pre-treated sludge (thermal-AD), respectively. Both alkaline/acid and thermal pre-treatments largely shifted sludge community composition and function, but in distinct ways, possibly due to their different sludge constitutes (i.e., dissolved organic matter and NaCl). Correspondingly, microbial network analysis identified three modules with varied keystone taxa and interaction patterns in the three digesters. Life cycle assessment showed the comparable environmental impacts of APAD, thermal-AD and control-AD. In all, this study provided a new solution for WAS treatment and insights into impact of sludge pre-treatments on sludge digestion microbiome.

Organic matter rather than salinity as a predominant feature changes performance and microbiome in methanogenic sludge digesters.

Due to low digestibility and long retention time of anaerobic sludge digestion, pre-treatment with alkaline/acid has been widely employed to enhance the rate and extent of sludge digestion. Nonetheless, effects of gradient concentrations of alkaline/acid pre-treatments and resulting salinity on digestion performance and sludge microbiome remain poorly understood. To elucidate these effects, both batch- and reactor-experiments were setup with varied feeding sludge. Significant digestion improvement and sludge microbiome changes were observed with alkaline/acid sludge pre-treatment, compared to non-pretreatment controls, e.g., ˜88% increase of carbon removal in sludge digesters. Surprisingly, with the same concentration of influent sludge, no notable change in digestion performance and sludge microbiome was observed in digesters when increasing alkaline/acid concentrations from 0.25 to 0.8 mol/L, and in batch serum bottles with or without NaCl amendment. Consequently, organic compounds dissolved in sludge pre-treatment could be a predominant selective pressure driving the performance and microbiome changes. By contrast, salinity as a consequence of the alkaline/acid pre-treatment could only enrich specific lineages, without altering the overall community profile and function. Together, this study provided insights into specific impacts of major factors on digester performance and sludge microbiome, and shed lights on optimization of sludge digestion.

Treatment of geometric singularities in implicit solvent models.

Geometric singularities, such as cusps and self-intersecting surfaces, are major obstacles to the accuracy, convergence, and stability of the numerical solution of the Poisson-Boltzmann (PB) equation. In earlier work, an interface technique based PB solver was developed using the matched interface and boundary (MIB) method, which explicitly enforces the flux jump condition at the solvent-solute interfaces and leads to highly accurate biomolecular electrostatics in continuum electric environments. However, such a PB solver, denoted as MIBPB-I, cannot maintain the designed second order convergence whenever there are geometric singularities, such as cusps and self-intersecting surfaces. Moreover, the matrix of the MIBPB-I is not optimally symmetrical, resulting in the convergence difficulty. The present work presents a new interface method based PB solver, denoted as MIBPB-II, to address the aforementioned problems. The present MIBPB-II solver is systematical and robust in treating geometric singularities and delivers second order convergence for arbitrarily complex molecular surfaces of proteins. A new procedure is introduced to make the MIBPB-II matrix optimally symmetrical and diagonally dominant. The MIBPB-II solver is extensively validated by the molecular surfaces of few-atom systems and a set of 24 proteins. Converged electrostatic potentials and solvation free energies are obtained at a coarse grid spacing of 0.5 A and are considerably more accurate than those obtained by the PBEQ and the APBS at finer grid spacings.

Treatment of charge singularities in implicit solvent models.

This paper presents a novel method for solving the Poisson-Boltzmann (PB) equation based on a rigorous treatment of geometric singularities of the dielectric interface and a Green's function formulation of charge singularities. Geometric singularities, such as cusps and self-intersecting surfaces, in the dielectric interfaces are bottleneck in developing highly accurate PB solvers. Based on an advanced mathematical technique, the matched interface and boundary (MIB) method, we have recently developed a PB solver by rigorously enforcing the flux continuity conditions at the solvent-molecule interface where geometric singularities may occur. The resulting PB solver, denoted as MIBPB-II, is able to deliver second order accuracy for the molecular surfaces of proteins. However, when the mesh size approaches half of the van der Waals radius, the MIBPB-II cannot maintain its accuracy because the grid points that carry the interface information overlap with those that carry distributed singular charges. In the present Green's function formalism, the charge singularities are transformed into interface flux jump conditions, which are treated on an equal footing as the geometric singularities in our MIB framework. The resulting method, denoted as MIBPB-III, is able to provide highly accurate electrostatic potentials at a mesh as coarse as 1.2 A for proteins. Consequently, at a given level of accuracy, the MIBPB-III is about three times faster than the APBS, a recent multigrid PB solver. The MIBPB-III has been extensively validated by using analytically solvable problems, molecular surfaces of polyatomic systems, and 24 proteins. It provides reliable benchmark numerical solutions for the PB equation.