Individual Microbial Cells Research Articles

Quantitative microbiology with widefield microscopy: navigating optical artefacts for accurate interpretations

Time-resolved live-cell imaging using widefield microscopy is instrumental in quantitative microbiology research. It allows researchers to track and measure the size, shape, and content of individual microbial cells over time. However, the small size of microbial cells poses a significant challenge in interpreting image data, as their dimensions approache that of the microscope’s depth of field, and they begin to experience significant diffraction effects. As a result, 2D widefield images of microbial cells contain projected 3D information, blurred by the 3D point spread function. In this study, we employed simulations and targeted experiments to investigate the impact of diffraction and projection on our ability to quantify the size and content of microbial cells from 2D microscopic images. This study points to some new and often unconsidered artefacts resulting from the interplay of projection and diffraction effects, within the context of quantitative microbiology. These artefacts introduce substantial errors and biases in size, fluorescence quantification, and even single-molecule counting, making the elimination of these errors a complex task. Awareness of these artefacts is crucial for designing strategies to accurately interpret micrographs of microbes. To address this, we present new experimental designs and machine learning-based analysis methods that account for these effects, resulting in accurate quantification of microbiological processes.

Single-cell transcriptomics across 2,534 microbial species reveals functional heterogeneity in the rumen microbiome.

Deciphering the activity of individual microbes within complex communities and environments remains a challenge. Here we describe the development of microbiome single-cell transcriptomics using droplet-based single-cell RNA sequencing and pangenome-based computational analysis to characterize the functional heterogeneity of the rumen microbiome. We generated a microbial genome database (the Bovine Gastro Microbial Genome Map) as a functional reference map for the construction of a single-cell transcriptomic atlas of the rumen microbiome. The atlas includes 174,531 microbial cells and 2,534 species, of which 172 are core active species grouped into 12 functional clusters. We detected single-cell-level functional roles, including a key role for Basfia succiniciproducens in the carbohydrate metabolic niche of the rumen microbiome. Furthermore, we explored functional heterogeneity and reveal metabolic niche trajectories driven by biofilm formation pathway genes within B. succiniciproducens. Our results provide a resource for studying the rumen microbiome and illustrate the diverse functions of individual microbial cells that drive their ecological niche stability or adaptation within the ecosystem.

ScMAR-Seq: a novel workflow for targeted single-cell genomics of microorganisms using radioactive labeling.

A central question in microbial ecology is which member of a community performs a particular metabolism. Several sophisticated isotope labeling techniques are available for analyzing the metabolic function of populations and individual cells in a community. However, these methods are generally either insufficiently sensitive or throughput-limited and thus have limited applicability for the study of complex environmental samples. Here, we present a novel approach that combines highly sensitive radioisotope tracking, microfluidics, high-throughput sorting, and single-cell genomics to simultaneously detect and identify individual microbial cells based solely on their in situ metabolic activity, without prior information on community structure.

Microbially mediated climate feedbacks from wetland ecosystems.

Wetlands are crucial nodes in the carbon cycle, emitting approximately 20% of global CH4 while also sequestering 20%-30% of all soil carbon. Both greenhouse gas fluxes and carbon storage are driven by microbial communities in wetland soils. However, these key players are often overlooked or overly simplified in current global climate models. Here, we first integrate microbial metabolisms with biological, chemical, and physical processes occurring at scales from individual microbial cells to ecosystems. This conceptual scale-bridging framework guides the development of feedback loops describing how wetland-specific climate impacts (i.e., sea level rise in estuarine wetlands, droughts and floods in inland wetlands) will affect future climate trajectories. These feedback loops highlight knowledge gaps that need to be addressed to develop predictive models of future climates capturing microbial contributions. We propose a roadmap connecting environmental scientific disciplines to address these knowledge gaps and improve the representation of microbial processes in climate models. Together, this paves the way to understand how microbially mediated climate feedbacks from wetlands will impact future climate change.

The Extracellular Matrix of Yeasts: A Key Player in the Microbial Biology Change of Paradigm.

Microbes are traditionally regarded as planktonic organisms, individual cells that live independently from each other. Although this is true, microbes in nature mostly live within large multi-species communities forming complex ecosystems. In these communities, microbial cells are held together and organised spatially by an extracellular matrix (ECM). Unlike the ECM from the tissues of higher eukaryotes, microbial ECM, mostly that of yeasts, is still poorly studied. However, microbial biofilms are a serious cause for concern, for being responsible for the development of nosocomial infections by pharmacological drugs-resistant strains of pathogens, or for critically threatening plant health and food security under climate change. Understanding the organization and behaviour of cells in biofilms or other communities is therefore of extreme importance. Within colonies or biofilms, extremely large numbers of individual microbial cells adhere to inert surfaces or living tissues, differentiate, die or multiply and invade adjacent space, often following a 3D architectural programme genetically determined. For all this, cells depend on the production and secretion of ECM, which might, as in higher eukaryotes, actively participate in the regulation of the group behaviour. This work presents an overview of the state-of-the-art on the composition and structure of the ECM produced by yeasts, and the inherent physicochemical properties so often undermined, as well as the available information on its production and delivery pathways.

Rapid Identification of Pathogens Causing Bloodstream Infections by Raman Spectroscopy and Raman Tweezers.

The search for the "Holy Grail" in clinical diagnostic microbiology-a reliable, accurate, low-cost, real-time, easy-to-use method-has brought up several methods with the potential to meet these criteria. One is Raman spectroscopy, an optical, nondestructive method based on the inelastic scattering of monochromatic light. The current study focuses on the possible use of Raman spectroscopy for identifying microbes causing severe, often life-threatening bloodstream infections. We included 305 microbial strains of 28 species acting as causative agents of bloodstream infections. Raman spectroscopy identified the strains from grown colonies, with 2.8% and 7% incorrectly identified strains using the support vector machine algorithm based on centered and uncentred principal-component analyses, respectively. We combined Raman spectroscopy with optical tweezers to speed up the process and captured and analyzed microbes directly from spiked human serum. The pilot study suggests that it is possible to capture individual microbial cells from human serum and characterize them by Raman spectroscopy with notable differences among different species. IMPORTANCE Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential. Therefore, our multidisciplinary team of microbiologists and physicists presents a method that reliably, rapidly, and inexpensively identifies pathogens causing bloodstream infections-Raman spectroscopy. We believe that it might become a valuable diagnostic tool in the future. Combined with optical trapping, it offers a new approach where the microorganisms are individually trapped in a noncontact way by optical tweezers and investigated by Raman spectroscopy directly in a liquid sample. Together with the automatic processing of measured Raman spectra and comparison with a database of microorganisms, it makes the whole identification process almost real time.

Label-Free Optical Imaging of the Electron Transfer in Single Live Microbial Cells.

Measurement of electron transfer at the single-particle or -cell level is crucial to the in situ study of basic chemical and biological processes. However, it remains challenging to directly probe the microbial extracellular electron transfer process due to the weakness of signals and the lack of techniques. Here, we present a label-free and noninvasive imaging method that is able to measure the electron transfer in microbial cells. We measured the extracellular electron transfer processes by imaging the redox reaction of c-type outer membrane cytochromes in microbial cells using a plasmonic imaging technique, and obtained the electrochemical activity parameters (formal potential and number of electrons transferred) of multiple individual microbial cells, allowing for unveiling ample heterogeneities in electron transfer at the single-cell level. We anticipate that this method will contribute to the study of electron transfer in various biological and chemical processes.

Decoupling of respiration rates and abundance in marine prokaryoplankton

The ocean–atmosphere exchange of CO2 largely depends on the balance between marine microbial photosynthesis and respiration. Despite vast taxonomic and metabolic diversity among marine planktonic bacteria and archaea (prokaryoplankton)1–3, their respiration usually is measured in bulk and treated as a ‘black box’ in global biogeochemical models4; this limits the mechanistic understanding of the global carbon cycle. Here, using a technology for integrated phenotype analyses and genomic sequencing of individual microbial cells, we show that cell-specific respiration rates differ by more than 1,000× among prokaryoplankton genera. The majority of respiration was found to be performed by minority members of prokaryoplankton (including the Roseobacter cluster), whereas cells of the most prevalent lineages (including Pelagibacter and SAR86) had extremely low respiration rates. The decoupling of respiration rates from abundance among lineages, elevated counts of proteorhodopsin transcripts in Pelagibacter and SAR86 cells and elevated respiration of SAR86 at night indicate that proteorhodopsin-based phototrophy3,5–7 probably constitutes an important source of energy to prokaryoplankton and may increase growth efficiency. These findings suggest that the dependence of prokaryoplankton on respiration and remineralization of phytoplankton-derived organic carbon into CO2 for its energy demands and growth may be lower than commonly assumed and variable among lineages.

Artificial intelligence-assisted automatic and index-based microbial single-cell sorting system for One-Cell-One-Tube.

Identification, sorting, and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes. In this work, based on an artificial intelligence (AI)-assisted object detection model for cell phenotype screening and a cross-interface contact method for single-cell exporting, we developed an automatic and index-based system called EasySort AUTO, where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed, "One-Cell-One-Tube" manner. The target cell is automatically identified based on an AI-assisted object detection model and then mobilized via an optical tweezer for sorting. Then, a cross-interface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube, which leads to coupling with subsequent single-cell culture or sequencing. The efficiency of the system for single-cell printing is >93%. The throughput of the system for single-cell printing is ~120 cells/h. Moreover, >80% of single cells of both yeast and Escherichia coli are culturable, suggesting the superior preservation of cell viability during sorting. Finally, AI-assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples, which was validated by downstream single-cell proliferation assays. The automation, index maintenance, and vitality preservation of EasySort AUTO suggest its excellent application potential for single-cell sorting.

High-resolution mass measurements of single budding yeast reveal linear growth segments

The regulation of cell growth has fundamental physiological, biotechnological and medical implications. However, methods that can continuously monitor individual cells at sufficient mass and time resolution hardly exist. Particularly, detecting the mass of individual microbial cells, which are much smaller than mammalian cells, remains challenging. Here, we modify a previously described cell balance (‘picobalance’) to monitor the proliferation of single cells of the budding yeast, Saccharomyces cerevisiae, under culture conditions in real time. Combined with optical microscopy to monitor the yeast morphology and cell cycle phase, the picobalance approaches a total mass resolution of 0.45 pg. Our results show that single budding yeast cells (S/G2/M phase) increase total mass in multiple linear segments sequentially, switching their growth rates. The growth rates weakly correlate with the cell mass of the growth segments, and the duration of each growth segment correlates negatively with cell mass. We envision that our technology will be useful for direct, accurate monitoring of the growth of single cells throughout their cycle.

Fast bacterial growth reduces antibiotic accumulation and efficacy.

Phenotypic variations between individual microbial cells play a key role in the resistance of microbial pathogens to pharmacotherapies. Nevertheless, little is known about cell individuality in antibiotic accumulation. Here, we hypothesise that phenotypic diversification can be driven by fundamental cell-to-cell differences in drug transport rates. To test this hypothesis, we employed microfluidics-based single-cell microscopy, libraries of fluorescent antibiotic probes and mathematical modelling. This approach allowed us to rapidly identify phenotypic variants that avoid antibiotic accumulation within populations of Escherichia coli, Pseudomonas aeruginosa, Burkholderia cenocepacia, and Staphylococcus aureus. Crucially, we found that fast growing phenotypic variants avoid macrolide accumulation and survive treatment without genetic mutations. These findings are in contrast with the current consensus that cellular dormancy and slow metabolism underlie bacterial survival to antibiotics. Our results also show that fast growing variants display significantly higher expression of ribosomal promoters before drug treatment compared to slow growing variants. Drug-free active ribosomes facilitate essential cellular processes in these fast-growing variants, including efflux that can reduce macrolide accumulation. We used this new knowledge to eradicate variants that displayed low antibiotic accumulation through the chemical manipulation of their outer membrane inspiring new avenues to overcome current antibiotic treatment failures.

Label-Free Raman Microspectroscopy for Identifying Prokaryotic Virocells.

ABSTRACTRaman microspectroscopy has been used to thoroughly assess growth dynamics and heterogeneity of prokaryotic cells, yet little is known about how the chemistry of individual cells changes during infection with virulent viruses, resulting in so-called virocells. Here, we investigate biochemical changes of bacterial and archaeal cells of three different species in laboratory cultures before and after addition of their respective viruses using single-cell Raman microspectroscopy. By applying multivariate statistics, we identified significant differences in the spectra of single cells with/without addition of virulent dsRNA phage (phi6) for Pseudomonas syringae. A general ratio of wavenumbers that contributed the greatest differences in the recorded spectra was defined as an indicator for virocells. Based on reference spectra, this difference is likely attributable to an increase in nucleic acid versus protein ratio of virocells. This method also proved successful for identification of Bacillus subtilis cells infected with the double-stranded DNA (dsDNA) phage phi29, displaying a decrease in respective ratio, but failed for archaeal virocells (Methanosarcina mazei with the dsDNA methanosarcina spherical virus) due to autofluorescence. Multivariate and univariate analyses suggest that Raman spectral data of infected cells can also be used to explore the complex biology behind viral infections of bacteria. Using this method, we confirmed the previously described two-stage infection of P. syringae’s phi6 and that infection of B. subtilis with phi29 results in a stress response within single cells. We conclude that Raman microspectroscopy is a promising tool for chemical identification of Gram-positive and Gram-negative virocells undergoing infection with virulent DNA or RNA viruses.IMPORTANCE Viruses are highly diverse biological entities shaping many ecosystems across Earth. However, understanding the infection of individual microbial cells and the related biochemical changes remains limited. Using Raman microspectroscopy in conjunction with univariate and multivariate statistics, we established a marker for identification of infected Gram-positive and Gram-negative bacteria. This nondestructive, label-free analytical method at single-cell resolution paves the way for future studies geared towards analyzing virus-host systems of prokaryotes to further understand the complex chemistry and function of virocells.

Application of microfluidic systems in modelling impacts of environmental structure on stress-sensing by individual microbial cells

Environmental structure describes physical structure that can determine heterogenous spatial distribution of biotic and abiotic (nutrients, stressors etc.) components of a microorganism’s microenvironment. This study investigated the impact of micrometre-scale structure on microbial stress sensing, using yeast cells exposed to copper in microfluidic devices comprising either complex soil-like architectures or simplified environmental structures. In the soil micromodels, the responses of individual cells to inflowing medium supplemented with high copper (using cells expressing a copper-responsive pCUP1-reporter fusion) could be described neither by spatial metrics developed to quantify proximity to environmental structures and surrounding space, nor by computational modelling of fluid flow in the systems. In contrast, the proximities of cells to structures did correlate with their responses to elevated copper in microfluidic chambers that contained simplified environmental structure. Here, cells within more open spaces showed the stronger responses to the copper-supplemented inflow. These insights highlight not only the importance of structure for microbial responses to their chemical environment, but also how predictive modelling of these interactions can depend on complexity of the system, even when deploying controlled laboratory conditions and microfluidics.

Calculation and Interpretation of Substrate Assimilation Rates in Microbial Cells Based on Isotopic Composition Data Obtained by nanoSIMS

Stable isotope probing (SIP) combined with nano-scale secondary ion mass spectrometry (nanoSIMS) is a powerful approach to quantify assimilation rates of elements such as C and N into individual microbial cells. Here, we use mathematical modeling to investigate how the derived rate estimates depend on the model used to describe substrate assimilation by a cell during a SIP incubation. We show that the most commonly used model, which is based on the simplifying assumptions of linearly increasing biomass of individual cells over time and no cell division, can yield underestimated assimilation rates when compared to rates derived from a model that accounts for cell division. This difference occurs because the isotopic labeling of a dividing cell increases more rapidly over time compared to a non-dividing cell and becomes more pronounced as the labeling increases above a threshold value that depends on the cell cycle stage of the measured cell. Based on the modeling results, we present formulae for estimating assimilation rates in cells and discuss their underlying assumptions, conditions of applicability, and implications for the interpretation of intercellular variability in assimilation rates derived from nanoSIMS data, including the impacts of storage inclusion metabolism. We offer the formulae as a Matlab script to facilitate rapid data evaluation by nanoSIMS users.

Single-Cell RNA Sequencing Elucidates the Structure and Organization of Microbial Communities.

Clonal bacterial populations exhibit various forms of heterogeneity, including co-occurrence of cells with different morphological traits, biochemical properties, and gene expression profiles. This heterogeneity is prevalent in a variety of environments. For example, the productivity of large-scale industrial fermentations and virulence of infectious diseases are shaped by cell population heterogeneity and have a direct impact on human life. Due to the need and importance to better understand this heterogeneity, multiple methods of examining single-cell heterogeneity have been developed. Traditionally, fluorescent reporters or probes are used to examine a specific gene of interest, providing a useful but inherently biased approach. In contrast, single-cell RNA sequencing (scRNA-seq) is an agnostic approach to examine heterogeneity and has been successfully applied to eukaryotic cells. Unfortunately, current extensively utilized methods of eukaryotic scRNA-seq present difficulties when applied to bacteria. Specifically, bacteria have a cell wall which makes eukaryotic lysis methods incompatible, bacterial mRNA has a shorter half-life and lower copy numbers, and isolating an individual bacterial species from a mixed community is difficult. Recent work has demonstrated that these technical hurdles can be overcome, providing valuable insight into factors influencing microbial heterogeneity. This perspective describes the emerging microbial scRNA-seq toolkit. We outline the benefit of these new tools in elucidating numerous scientific questions in microbiological studies and offer insight about the possible rules that govern the segregation of traits in individual microbial cells.

Microbial Interaction with Clay Minerals and Its Environmental and Biotechnological Implications

Clay minerals are very common in nature and highly reactive minerals which are typical products of the weathering of the most abundant silicate minerals on the planet. Over recent decades there has been growing appreciation that the prime involvement of clay minerals in the geochemical cycling of elements and pedosphere genesis should take into account the biogeochemical activity of microorganisms. Microbial intimate interaction with clay minerals, that has taken place on Earth’s surface in a geological time-scale, represents a complex co-evolving system which is challenging to comprehend because of fragmented information and requires coordinated efforts from both clay scientists and microbiologists. This review covers some important aspects of the interactions of clay minerals with microorganisms at the different levels of complexity, starting from organic molecules, individual and aggregated microbial cells, fungal and bacterial symbioses with photosynthetic organisms, pedosphere, up to environmental and biotechnological implications. The review attempts to systematize our current general understanding of the processes of biogeochemical transformation of clay minerals by microorganisms. This paper also highlights some microbiological and biotechnological perspectives of the practical application of clay minerals–microbes interactions not only in microbial bioremediation and biodegradation of pollutants but also in areas related to agronomy and human and animal health.

Effect of medial-lateral hand positions on glenohumeral and acromioclavicular joint kinematics during push-up exercise

Chemical sensing is an important yet less developed part of Internet of things technology as it generates chemical information that is highly relevant in environment monitoring, public health, and industrial safety. To this end, nano-electronic sensory and signal transmission devices have the best technological and commercial potential for its compatibility with the existing electronic devices. The search for suitable and high-performance sensing materials and their proper incorporations into the micro-/nano-electronic platforms hold the key. For materials, nanocomposites based on graphitic carbon nanomaterials and other functional building blocks, one for signal transduction and one for molecular recognition, respectively, have achieved tremendous success in the application of chemical sensors and energy devices due to their tunable complexity and functionality. Here we summarize the design, synthesis, and device fabrication of nanocomposite materials based on single-walled carbon nanotubes and graphene, with functional building blocks including conducting polymers, metal, metal oxide, etc. Novel chemical approaches have been developed for the assembly of different building blocks, as well as their applications in chemical sensing, breath diagnostics, and energy applications. Based on the fundamental working principles of nano-electronic chemical sensing, we further demonstrate an on-chip nano-electronic-based chemical signaling technique for the investigation and improvement of sustainable energy technologies. Through the development of a novel on-chip electrical transport spectroscopy approach, we demonstrate that the electrical properties of ultrafine platinum nanowires are highly sensitive and selective to the electrochemical surface states, enabling an in situ nano-electronic signaling pathway that reveals electrochemical interface information in various energy conversion reactions. Through the new insights and newly identified nano-electronic indicators, we further demonstrate the rationally designed strategies for enhanced performance (activity, poisoning resistance, and lifetime) of energy conversion devices. Furthermore, systematic on-chip nano-electronic investigations of bioelectrochemical systems help to elucidate the complex basis of electrical conductivity of both individual microbial cells and biofilms, which will accelerate our basic understanding of earth’s microbiomes and harness the capabilities of microbial ecosystems.

Effect of design of assisting devices on the lower body muscular activities during gait with crutch executed by amputees

Chemical sensing is an important yet less developed part of Internet of things technology as it generates chemical information that is highly relevant in environment monitoring, public health, and industrial safety. To this end, nano-electronic sensory and signal transmission devices have the best technological and commercial potential for its compatibility with the existing electronic devices. The search for suitable and high-performance sensing materials and their proper incorporations into the micro-/nano-electronic platforms hold the key. For materials, nanocomposites based on graphitic carbon nanomaterials and other functional building blocks, one for signal transduction and one for molecular recognition, respectively, have achieved tremendous success in the application of chemical sensors and energy devices due to their tunable complexity and functionality. Here we summarize the design, synthesis, and device fabrication of nanocomposite materials based on single-walled carbon nanotubes and graphene, with functional building blocks including conducting polymers, metal, metal oxide, etc. Novel chemical approaches have been developed for the assembly of different building blocks, as well as their applications in chemical sensing, breath diagnostics, and energy applications. Based on the fundamental working principles of nano-electronic chemical sensing, we further demonstrate an on-chip nano-electronic-based chemical signaling technique for the investigation and improvement of sustainable energy technologies. Through the development of a novel on-chip electrical transport spectroscopy approach, we demonstrate that the electrical properties of ultrafine platinum nanowires are highly sensitive and selective to the electrochemical surface states, enabling an in situ nano-electronic signaling pathway that reveals electrochemical interface information in various energy conversion reactions. Through the new insights and newly identified nano-electronic indicators, we further demonstrate the rationally designed strategies for enhanced performance (activity, poisoning resistance, and lifetime) of energy conversion devices. Furthermore, systematic on-chip nano-electronic investigations of bioelectrochemical systems help to elucidate the complex basis of electrical conductivity of both individual microbial cells and biofilms, which will accelerate our basic understanding of earth’s microbiomes and harness the capabilities of microbial ecosystems.

Raman spectroscopic signatures of carotenoids and polyenes enable label-free visualization of microbial distributions within pink biofilms

Pink biofilms are multispecies microbial communities that are commonly found in moist household environments. The development of this pink stain is problematic from an aesthetic point of view, but more importantly, it raises hygienic concerns because they may serve as a potential reservoir of opportunistic pathogens. Although there have been several studies of pink biofilms using molecular analysis and confocal laser scanning microscopy, little is known about the spatial distributions of constituent microorganisms within pink biofilms, a crucial factor associated with the characteristics of pink biofilms. Here we show that Raman spectroscopic signatures of intracellular carotenoids and polyenes enable us to visualize pigmented microorganisms within pink biofilms in a label-free manner. We measured space-resolved Raman spectra of a pink biofilm collected from a bathroom, which clearly show resonance Raman bands of carotenoids. Multivariate analysis of the Raman hyperspectral imaging data revealed the presence of typical carotenoids and structurally similar but different polyenes, whose spatial distributions within the pink biofilm were found to be mutually exclusive. Raman measurements on individual microbial cells isolated from the pink biofilm confirmed that these distributions probed by carotenoid/polyene Raman signatures are attributable to different pigmented microorganisms. The present results suggest that Raman microspectroscopy with a focus on microbial pigments such as carotenoids is a powerful nondestructive method for studying multispecies biofilms in various environments.

Up-scaling microbial fuel cell systems for the treatment of real textile dye wastewater and bioelectricity recovery

ABSTRACT In this work the energy recovery in microbial fuel cell was studied by electrically stacking its three individual units into series and parallel arrangements. The power output was higher in parallel stacking by 2.07 and 14.77 times than series and individual units respectively. The rate of degradation of dye wastewater was in order of individual Microbial Fuel Cell (MFC) < series stack < parallel stack. The corn cob biochar was used as an additive in the MFC to improve the efficiency of the individual MFC unit. The addition of 0.5 g corn cob biochar enhanced the power output to 38.6 mW/m2 from 0.47 mW/m2 in the MFC individual unit without the biochar additive. The simultaneous COD reduction, TDS reduction and decolourisation of dye wastewater achieved are 82.14%, 68% and 74.8% respectively. The current work demonstrates that the dose of biochar and parallel stacking are a framework to achieve enhanced dye removal and bioenergy recovery via microbial fuel cell.