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Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms, and how microbes in these environments exchange these molecules remains elusive for many of these bioactive species due to non-efficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium bromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilisNCIB 3610) and fungus (Fusariumsp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl-groups within this model system. Various spatial patterns are observable of these species, which indicate possible extracellular or intercellular processes of the metabolites, and their up or down regulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in thisB. subtilis/Fusariumsp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OCTD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interactions studies with expanded metabolic coverage.IMPORTANCEThe metabolic profiles within microbial biofilms and interkingdom interactions are extremely complex and serve a variety of functions, which include promoting colonization, growth, and survival within competitive and symbiotic environments. However, measuringanddifferentiating many of these molecules, especially in anin-situfashion, remains a significant analytical challenge. We demonstrate a chemical derivatization strategy that enabled highly sensitive, multiplexed mass spectrometry imaging of over 300 metabolites from a model microbial co-culture. Notably, this approach afforded us to visualize over two dozen classes of ketone-, aldehyde-, and carboxyl-containing molecules, which were previously undetectable from colonies grown on agar. We also demonstrate that this chemical derivatization strategy can enable discrimination of isobaric and isomeric metabolites, without the need for orthogonal separation (e.g.,online chromatography or ion mobility). We anticipate this approach will further enhance our knowledge of metabolic regulation within microbiomes and microbial systems used in bioengineering applications.

Communities of soil microorganisms (soil microbiomes) play a major role in biogeochemical cycles and support of plant growth. Here we focus primarily on the roles that the soil microbiome plays in cycling soil organic carbon and the impact of climate change on the soil carbon cycle. We first discuss current challenges in understanding the roles carried out by highly diverse and heterogeneous soil microbiomes and review existing knowledge gaps in understanding how climate change will impact soil carbon cycling by the soil microbiome. Because soil microbiome stability is a key metric to understand as the climate changes, we discuss different aspects of stability, including resistance, resilience, and functional redundancy.We then review recent research pertaining to the impact of major climate perturbations on the soil microbiome and the functions that they carry out. Finally, we review new experimental methodologies and modeling approaches under development that should facilitate our understanding of the complex nature of the soil microbiome to better predict its future responses to climate change.

Contaminated wastewater is a serious threat to different fragile ecosystems and related life forms. The presence of microorganisms, such as bacteria, fungi, yeast, and viruses in water is harmful for humans. Contaminated water containing several pathogenic bacteria act as the vehicle for several infectious diseases. Neutralization and removal of these pathogens before discharging into stream water or using them for other purposes is inevitable. Several molecular biology techniques are employed for detection of these pathogens. Specific biomolecules at the microbial surface may be used for the detection of pathogens by tagging sensors molecules such as antibodies, aptamers, carbohydrates, and antimicrobial peptides with different nanoparticles.

In beam-based ionization methods, the substrate plays an important role on the desorption mechanism of molecules from surfaces. Both the specific orientation that a molecule adopts at a surface and the strength of the molecule-surface interaction can greatly influence desorption processes, which in turn will affect the ion yield and the degree of in-source fragmentation of a molecule. In the beam-based method of secondary ion mass spectrometry (SIMS), in-source fragmentation can be significant and molecule specific due to the hard ionization method of using a primary ion beam for molecule desorption. To investigate the role of the substrate on orientation and in-source fragmentation, we have used atomistic simulations—molecular dynamics in combination with density functional theory calculations—to explore the desorption of a sphingolipid (palmitoylsphingomyelin) from a model surface (gold). We then compare SIMS data from this model system to our modeling findings. Using this approach, we found that the combined adsorption and binding energy of certain bonds associated with the headgroup fragments (C3H8N+, C5H12N+, C5H14NO+, and C5H15PNO4+) was a good predictor for fragment intensities (as indicated by relative ion yields). This is the first example where atomistic simulations have been applied in beam-based ionization of lipids, and it presents a new approach to study biointerfacial lipid ordering effects on SIMS imaging.

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils, because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hotspots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood. Here, we addressed this knowledge gap by directly visualizing nutrient acquisition and transport through fungal hyphae in a mineral doped soil micromodel using a multimodal imaging approach. We observed thatFusarium sp. DS 682, a representative of common saprotrophic soil fungi, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (∼12 µm) in the presence of minerals. The fungus incorporated and translocated potassium (K) from K-rich mineral interfaces, as evidenced by visualization of mineral derived nutrient transport and unique K chemical moieties following fungal induced mineral weathering. Specific membrane transport proteins were expressed in the presence of minerals, including those involved in oxidative phosphorylation pathways and transmembrane transport of small molecular weight organic acids. This study establishes the significance of fungal biology and nutrient translocation mechanisms in maintaining fungal growth under water and nutrient limitations in a soil-like microenvironment.

Mass spectrometry imaging (MSI) is becoming an increasingly popular analytical technique to investigate microbial systems. However, differences in the ionization efficiencies of distinct MSI methods lead to biases in terms of what types and classes of molecules can be detected. Here, we sought to increase the molecular coverage of microbial colonies by employing metal-assisted laser desorption/ionization (MetA-LDI) MSI, and we compared our results to more commonly utilized matrix-assisted laser desorption/ionization MALDI MSI. We found substantial (∼67%) overlap in the molecules detected in our analysis of Bacillus subtilis colony biofilms using both methods, but each ionization technique did lead to the identification of a unique subset of molecular species. MetA-LDI MSI tended to identify more small molecules and neutral lipids, whereas MALDI MSI more readily detected other lipids and surfactin species. Putative annotations were made using METASPACE, Metlin, and the BsubCyc database. These annotations were then confirmed from analyses of replicate bacterial colonies using liquid extraction surface analysis tandem mass spectrometry. Additionally, we analyzed B. subtilis biofilms in a polymer-based emulated soil micromodel using MetA-LDI MSI to better understand bacterial processes and metabolism in a native, soil-like environment. We were able to detect different molecular signatures within the micropore regions of the micromodel. We also show that MetA-LDI MSI can be used to analyze microbial biofilms from electrically insulating material. Overall, this study expands the molecular universe of microbial metabolism that can be visualized by MSI. IMPORTANCE Matrix-assisted laser desorption/ionization mass spectrometry imaging is becoming an important technique to investigate molecular processes within microbial colonies and microbiomes under different environmental conditions. However, this method is limited in terms of the types and classes of molecules that can be detected. In this study, we utilized metal-assisted laser desorption/ionization mass spectrometry imaging, which expanded the range of molecules that could be imaged from microbial samples. One advantage of this technique is that the addition of a metal helps facilitate ionization from electrically nonconductive substrates, which allows for the investigation of biofilms grown in polymer-based devices, like soil-emulating micromodels.

The novel fungal strain, Fusarium sp. strain DS 682, was isolated from the rhizosphere of the perennial grass, Bouteloua gracilis, at the Konza Prairie Biological Station in Kansas. This fungal strain is common across North American grasslands and is resilient to environmental fluctuations. The draft genome is estimated to be 97.2% complete.

The novel fungal strain, Fusarium sp. strain DS 682, was isolated from the rhizosphere of the perennial grass, Bouteloua gracilis , at the Konza Prairie Biological Station in Kansas. This fungal strain is common across North American grasslands and is resilient to environmental fluctuations. The draft genome is estimated to be 97.2% complete.

Water bodies get contaminants from natural and anthropogenic sources. Infectious ingredients of wastewater are released from hospitals, veterinary clinics, households, and industries and are harmful to the aquatic ecosystem. Aquatic animals are more vulnerable to these contaminants because of direct exposure to harmful to the water bodies. Different approaches, such as Ames bioassay, comet assay, and luminescent biosensor, are routine monitoring tools to assay infectious contaminants in wastewater effluents. The proposed chapter aims to review the classical and emerging approaches to assay the contaminants present in the wastewater. The source and type of contaminants will also be described. The emerging “-omics” technology including metagenomics, transcriptomics, metatranscriptomics, and metabolomics for toxicological assessment of water and other environmental samples will also be discussed. The discussion will cover the assay method for both culturable and nonculturable microbial contaminants for detection. All emerging methods such as high-throughput next-generation sequencing as well as fluorescence in situ hybridization, denaturant gradient gel electrophoresis, and biosensors will also be detailed in the current chapter.

Nanomaterials are increasingly used in various biomedical applications including detection and diagnostic purposes. This field is advancing at high pace and we aim to update the role of microbial nanotechnology, especially in the diagnostic applications related topics. A detailed coverage of the microbial synthesis of nanoparticles, diagnostic applications of nanoparticles including magnetic, metallic, fluorescent, peptide, and polymer-based nanoparticles is provided. Further, an assessment of benefit and limitation of diagnostic technology based on microbial nanotechnology is provided. Other than detection, a few non-patient applications for infection management are also presented like sterilization of medical implants, prevention of nosocomial infections, and nano-formulated vaccines.

Majority of the industrial products are made in variety of extreme environments. These industrial processes generate by-products that are difficult to degrade, harmful for environment, and toxic to animals and humans. These industrial by-products are present in extreme conditions such as high salt and high or low temperature. It is an unfavorable condition for most of the waste-degrading enzymes as they work at ambient condition. The harmful industrial by-products, therefore, needed to shift at ambient condition for their degradation. Extremophiles grow at extreme conditions, and so their enzymes too work optimally under these extreme conditions. Extremophiles have enormous potential in biotechnological industry and waste remediation/management. Some halophilic microorganisms have great efficiency to remove petroleum, heavy metals, and dyes from the water polluted by industries. The chapter details the protein adaptations in different extremophiles for their survival and uses of different extremophilic organisms/proteins in bioremediation.

Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved., Understanding the basic biology that underpins soil microbiome interactions is required to predict the metaphenomic response to environmental shifts. A significant knowledge gap remains in how such changes affect microbial community dynamics and their metabolic landscape at microbially relevant spatial scales. Using a custom-built SoilBox system, here we demonstrated changes in microbial community growth and composition in different soil environments (14%, 24%, and 34% soil moisture), contingent upon access to reservoirs of nutrient sources. The SoilBox emulates the probing depth of a common soil core and enables determination of both the spatial organization of the microbial communities and their metabolites, as shown by confocal microscopy in combination with mass spectrometry imaging (MSI). Using chitin as a nutrient source, we used the SoilBox system to observe increased adhesion of microbial biomass on chitin islands resulting in degradation of chitin into N-acetylglucosamine (NAG) and chitobiose. With matrix-assisted laser desorption/ionization (MALDI)-MSI, we also observed several phospholipid families that are functional biomarkers for microbial growth on the chitin islands. Fungal hyphal networks bridging different chitin islands over distances of 27 mm were observed only in the 14% soil moisture regime, indicating that such bridges may act as nutrient highways under drought conditions. In total, these results illustrate a system that can provide unprecedented spatial information about interactions within soil microbial communities as a function of changing environments. We anticipate that this platform will be invaluable in spatially probing specific intra- and interkingdom functional relationships of microbiomes within soil. IMPORTANCE Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved.

Here we show a synthetic system that uses reaction and diffusion to both grow new material via polymerization and remove material through polymer chain breakage—mimicking the process of bone remodeling in a synthetic system. Researchers have explored the use of reaction/diffusion systems to pattern microstructures with success, but very little work focuses on using these processes to shape microstructures in a dynamic manner. This report provides an example of a dynamic system that can reshape itself using diffusion gradients. Mimicking this dynamic process could enable the development of materials that strengthen in response to repeated application of stress and are able to undergo remodeling after initial fabrication.

Detection of bacterial metabolites at low concentrations in fluids with complex background allows for applications ranging from detecting biomarkers of respiratory infections to identifying contaminated medical instruments. Surface-enhanced Raman scattering (SERS) spectroscopy, when utilizing plasmonic nanogaps, has the relatively unique capacity to reach trace molecular detection limits in a label-free format, yet large-area device fabrication incorporating nanogaps with this level of performance has proven difficult. Here, we demonstrate the advantages of using chemical assembly to fabricate SERS surfaces with controlled nanometer gap spacings between plasmonic nanospheres. Control of nanogap spacings via the length of the chemical crosslinker provides uniform SERS signals, exhibiting detection of pyocyanin, a secondary metabolite of Pseudomonas aeruginosa, in aqueous media at concentration of 100 pg·mL-1. When using machine learning algorithms to analyze the SERS data of the conditioned medium from a bacterial culture, having a more complex background, we achieve 1 ng·mL-1 limit of detection of pyocyanin and robust quantification of concentration spanning 5 orders of magnitude. Nanogaps are also incorporated in an in-line microfluidic device, enabling longitudinal monitoring of P. aeruginosa biofilm formation via rapid pyocyanin detection in a medium effluent as early as 3 h after inoculation and quantification in under 9 h. Surface-attached bacteria exposed to a bactericidal antibiotic were differentially less susceptible after 10 h of growth, indicating that these devices may be useful for early intervention of bacterial infections.

Bacteria form interface-associated communities called biofilms, often comprising multiple species. Biofilms can be detrimental or beneficial in medical, industrial, and technological settings, and their stability and function are determined by interspecies communication via specific chemical signaling or metabolite exchange. The deterministic control of biofilm development, behavior, and properties remains an unmet challenge, limiting our ability to inhibit the formation of detrimental biofilms in biomedical settings and promote the growth of beneficial biofilms in biotechnology applications. Here, we describe the development of growth surfaces that promote the growth of commensal Escherichia coli instead of the opportunistic pathogen Pseudomonas aeruginosa. Periodically patterned growth surfaces induced robust morphological changes in surface-associated E. coli biofilms and influenced the antibiotic susceptibilities of E. coli and P. aeruginosa biofilms. Changes in the biofilm architecture resulted in the accumulation of a metabolite, indole, which controls the competition dynamics between the two species. Our results show that the surface on which a biofilm grows has important implications for species colonization, growth, and persistence when exposed to antibiotics.

The adaptability of soil microbial communities to prolonged periods of drought is influenced by their ability to produce extracellular polymeric substances (EPS) with sufficient water retention properties. Microbial EPS have been extensively investigated as water reservoirs during drought, but it remains unknown how carbon substrate accessibility to soil microbial communities will affect the chemical properties of the EPS they generate, and whether this in turn will alter their water retention characteristics. In this work, we observed that the accessibility of carbon substrates influenced microbial community structure and, consequently, the chemical properties of EPS produced by the microbial communities. Our results demonstrated that an insoluble carbon substrate (i.e., chitin), stimulated microbial communities to produce EPS with measurably better water retention properties in emulated soil microenvironments in comparison to a soluble carbon substrate (i.e., N-acetylglucosamine; NAG). In all, this study demonstrates the importance of carbon substrate accessibility by soil microorganisms in regulating the community structure and consequently, the EPS carbon chemistry, which in turn can greatly influence the adaptability of soil microbial communities to drought.

Bacterial biofilms are problematic in natural and anthropogenic environments, and they confer protective properties on their constituent cells, making them difficult to treat with conventional antibiotics. Antibiofilm strategies, therefore, represent a promising direction of research for treating biofilm infections. Natural autodispersal and interspecies dispersal signaling pathways provide insight into cell-cell communication mechanisms, species dynamics in mixed communities, and potential targets for infection therapies. Here, we describe a novel interspecies dispersal signaling pathway between Pseudomonas aeruginosa and Escherichia coli. E. coli biofilms disperse in response to compounds in P. aeruginosa culture supernatant. Two components of the P. aeruginosa Las and Rhl quorum sensing systems, N-(3-oxo-dodecanoyl) homoserine lactone (3oxoC12HSL) and rhamnolipids, are found to act cooperatively to disperse E. coli biofilms. Our results indicate that rhamnolipids do not affect growth, biofilm development, or dispersal in E. coli but instead complement 3oxoC12HSL signaling by inducing selective permeability of the E. coli membrane. The increased target cell permeability is consistent with rhamnolipid-mediated removal of lipopolysaccharide from E. coli membranes and appears to selectively increase the permeability of lipophilic acyl homoserine lactones. This work suggests that rhamnolipids play a critical role in P. aeruginosa-E. coli interspecies signaling. Rhamnolipids and other biosurfactants may have similar effects in other intra- and interspecies chemical signaling pathways.

Pseudomonas aeruginosa is an opportunistic, biofilm-forming pathogen. P. aeruginosa produces pyocyanin, a secondary metabolite as part of its quorum sensing signaling system activated during biofilm formation. Self-organized plasmonic nanogaps provide enhancements to Raman scattering signals to achieve 10 ng/mL limit of detection of pyocyanin that enables early detection of biofilm formation. We report, for the first time, in-line biofilm detection in microfluidic channels as early as three hours from the onset of bacterial culturing and quantification spanning five-orders of magnitude of pyocyanin concentration during biofilm formation of PA14.

Bacterial populations exhibit a range of metabolic states influenced by their environment, intra- and interspecies interactions. The identification of bacterial metabolic states and transitions between them in their native environment promises to elucidate community behavior and stochastic processes, such as antibiotic resistance acquisition. In this work, we employ two-photon fluorescence lifetime imaging microscopy (FLIM) to create a metabolic fingerprint of individual bacteria and populations. FLIM of autofluorescent reduced nicotinamide adenine dinucleotide (phosphate), NAD(P)H, has been previously exploited for label-free metabolic imaging of mammalian cells. However, NAD(P)H FLIM has not been established as a metabolic proxy in bacteria. Applying the phasor approach, we create FLIM-phasor maps of Escherichia coli, Salmonella enterica serovar Typhimurium, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus epidermidis at the single cell and population levels. The bacterial phasor is sensitive to environmental conditions such as antibiotic exposure and growth phase, suggesting that observed shifts in the phasor are representative of metabolic changes within the cells. The FLIM-phasor approach represents a powerful, non-invasive imaging technique to study bacterial metabolism in situ and could provide unique insights into bacterial community behavior, pathology and antibiotic resistance with sub-cellular resolution.

Pseudomonas aeruginosa (PA), a biofilm forming bacterium, commonly affects cystic fibrosis, burn victims, and immunocompromised patients. PA produces pyocyanin, an aromatic, redox active, secondary metabolite as part of its quorum sensing signaling system activated during biofilm formation. Surface enhanced Raman scattering (SERS) sensors composed of Au nanospheres chemically assembled into clusters on diblock copolymer templates were fabricated and the ability to detect pyocyanin to monitor biofilm formation was investigated. Electromagnetic full wave simulations of clusters observed in scanning electron microcopy images show that the localized surface plasmon resonance wavelength is 696 nm for a dimer with a gap spacing of 1 nm in an average dielectric environment of the polymer and analyte; the local electric field enhancement is on the order of 400 at resonance, relative to free space. SERS data acquired at 785 nm excitation from a monolayer of benzenethiol on fabricated samples was compared with Raman data of pure benzenethiol and enhancement factors as large as 8×10 9 were calculated that are consistent with simulated field enhancements. Using this system, the limit of detection of pyocyanin in pure gradients was determined to be 10 parts per billion. In SERS data of the supernatant from the time dependent growth of PA shaking cultures, pyocyanin vibrational modes were clearly observable during the logarithmic growth phase corresponding to activation of genes related to biofilm formation. These results pave the way for the use of SERS sensors for the early detection of biofilm formation, leading to reduced healthcare costs and better patient outcomes.

While a large number of bacteria are deemed beneficial, there is an increasing number of strains associated with pathology, including life-threatening diseases. Moreover, during the last decade, a large number of new infectious strains have been discovered. Treatment is often hindered by emergence multi-drug resistant bacterial strains. Bacteria adapt to adverse environmental conditions by changing their metabolic activity. Further, there also exists metabolic diversity within the same population. Non-invasive assessment of bacterial metabolism could shed light on their physiological status. In this work we employ two-photon fluorescence lifetime imaging microscopy (FLIM) of live, clinically relevant bacteria. FLIM of autofluorescent metabolic coenzyme reduced nicotinamide adenine dinucleotide (phosphate), NAD(P)H, has been extensively exploited for label-free metabolic imaging of mammalian cells to study cancer and other diseases. However, it has not been explored to similar extents in bacteria. We apply phasor analysis to FLIM and create FLIM-phasor fingerprints of bacteria species Escherichia coli, Salmonella enterica serovar Typhimurium, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus epidermidis. The FLIM-phasor method also allows metabolic fingerprinting of individual bacteria within a population. We demonstrate that the NAD(P)H FLIM-phasor fingerprint of bacteria is sensitive to bacteriostatic and bactericidal antibiotics treatment. Furthermore, it varied with cell growth phase of planktonic cultures, suggesting that characteristic shifts in the NAD(P)H FLIM-phasor are representative of modulation of metabolic state of the cells. The FLIM-phasor approach represents a powerful non-invasive imaging technique to study bacterial metabolism and characterize the phasor fingerprint of bacteria under various conditions. This method could prove important in understanding bacteria related pathology, drug response and therapy as well as emergence of newer drug-resistant bacterial strains, all in a label-free manner.Work supported in part by NIH grants P50GM076516,P41GM103540

Automated spraying devices have become ubiquitous in laboratories employing matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time-consuming and can lead to overall nonoptimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirty-two combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 T Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal delocalization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other matrix application approaches and MALDI-MSI analyses of other molecular classes and tissue types.