Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, impacting measurement robustness, quantification and throughput. Here, we coupled LCM with a proteomics workflow that provides fully automated analysis of proteomes from microdissected tissues. Benchmarking against the current state-of-the-art in ultrasensitive global proteomics (FASP workflow), our approach demonstrated significant improvements in quantification (~2-fold lower variance) and throughput (>5 times faster). Using our approach we for the first time characterized, to a depth of >3,400 proteins, the ontogeny of protein changes during normal lung development in microdissected alveolar tissue containing only 4,000 cells. Our analysis revealed seven defined modules of coordinated transcription factor-signaling molecule expression patterns, suggesting a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes.

Global proteomic analyses of complex protein samples in nanogram quantities require a fastidious approach to achieve in-depth protein coverage and quantitative reproducibility. Biological samples are often severely mass limited and can preclude the application of more robust bulk sample processing workflows. In this study, we present a system that minimizes sample handling by using online immobilized trypsin digestion and solid phase extraction to create a simple, sensitive, robust, and reproducible platform for the analysis of nanogram-size proteomic samples. To demonstrate the effectiveness of our simplified nanoproteomics platform, we used the system to analyze preimplantation blastocysts collected on day 4 of pregnancy by flushing the uterine horns with saline. For each of our three sample groups, blastocysts were pooled from three mice resulting in 22, 22, and 25 blastocysts, respectively. The resulting proteomic data provide novel insight into mouse blastocyst protein expression on day 4 of normal pregnancy because we characterized 348 proteins that were identified in at least two sample groups, including 59 enzymes and blastocyst specific proteins (eg, zona pellucida proteins). This technology represents an important advance in which future studies could perform global proteomic analyses of blastocysts obtained from an individual mouse, thereby enabling researchers to investigate interindividual variation as well as increase the statistical power without increasing animal numbers. This approach is also easily adaptable to other mass-limited sample types.

Herbivores use symbiotic microbes to help derive energy and nutrients from plant material. Leaf-cutter ants are a paradigmatic example, cultivating their mutualistic fungus Leucoagaricus gongylophorus on plant biomass that workers forage from a diverse collection of plant species. Here, we investigate the metabolic flexibility of the ants’ fungal cultivar for utilizing different plant biomass. Using feeding experiments and a novel approach in metaproteomics, we examine the enzymatic response of L. gongylophorus to leaves, flowers, oats, or a mixture of all three. Across all treatments, our analysis identified and quantified 1,766 different fungal proteins, including 161 putative biomass-degrading enzymes. We found significant differences in the protein profiles in the fungus gardens of sub-colonies fed different plant substrates. When provided with leaves or flowers, which contain the majority of their energy as recalcitrant plant polymers, the fungus gardens produced more proteins predicted to break down cellulose: endoglucanase, exoglucanase, and β-glucosidase. Further, the complete metaproteomes for the leaves and flowers treatments were very similar, while the mixed substrate treatment closely resembled the treatment with oats alone. This indicates that when provided a mixture of plant substrates, fungus gardens preferentially break down the simpler, more digestible substrates. This flexible, substrate-specific enzymatic response of the fungal cultivar allows leaf-cutter ants to derive energy from a wide range of substrates, which likely contributes to their ability to be dominant generalist herbivores.

Leaf-cutter ants are dominant herbivores in ecosystems throughout the Neotropics that feed on fungus gardens cultivated on fresh foliar biomass. Although recent investigations have shed light on how plant biomass is degraded in fungus gardens, the cycling of nutrients that takes place in these specialized microbial ecosystems is still not well understood. Here, using metabolomic and metaproteomic techniques, we examine the dynamics of nutrient turnover in these gardens. Our results reveal that numerous free amino acids and sugars are depleted throughout the process of biomass degradation, indicating that easily accessible nutrients from plant material are readily consumed by microbes in these ecosystems. Accumulation of cellobiose and lignin derivatives near the end of the degradation process is consistent with previous characterization of lignocellulases produced by the fungal cultivar of the ants. Our results also suggest that ureides may be an important source of nitrogen in fungus gardens, especially during nitrogen-limiting conditions. No free arginine was detected in our metabolomic experiments despite evidence that the host ants cannot produce this amino acid, suggesting that biosynthesis of this metabolite may be tightly regulated in fungus gardens. These results provide new insights into microbial community-level processes that underlie this important ant-fungus symbiosis.

Mass spectrometry (MS) measurements are not inherently calibrated. Researchers use various calibration methods to assign meaning to arbitrary signal intensities and improve precision. Internal calibration (IC) methods use internal standards (IS) such as synthesized or recombinant proteins or peptides to calibrate MS measurements by comparing endogenous analyte signal to the signal from known IS concentrations spiked into the same sample. However, recent work suggests that using IS as IC introduces quantitative biases that affect comparison across studies because of the inability of IS to capture all sources of variation present throughout an MS workflow. Here, we describe a single-point external calibration strategy to calibrate signal intensity measurements to a common reference material, placing MS measurements on the same scale and harmonizing signal intensities between instruments, acquisition methods, and sites. We demonstrate data harmonization between laboratories and methodologies using this generalizable approach.