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bThe consequences of cellular heterogeneity, such as biocide persistence, can only be tackled by studying each individual in a cell population. Fluorescent tags provide tools for the high-throughput analysis of genomes, RNA transcripts, or proteins on the single-cell level. However, the analysis of lower-molecular-weight compounds that elude tagging is still a great challenge. Here, we describe a novel high-throughput microscale sample preparation technique for single cells that allows a mass spectrum to be obtained for each individual cell within a microbial population. The approach presented includes spotting Chlamydomonas reinhardtii cells, using a noncontact microarrayer, onto a specialized slide and controlled lysis of cells separated on the slide. Throughout the sample preparation, analytes were traced and individual steps optimized using autofluorescence detection of chlorophyll. The lysates of isolated cells are subjected to a direct, label-free analysis using matrix-assisted laser desorption ionization mass spectrometry. Thus, we were able to differentiate individual cells of two Chlamydomonas reinhardtii strains based on single-cell mass spectra. Furthermore, we showed that only population profiles with real single-cell resolution render a nondistorted picture of the phenotypes contained in a population. Heterogeneity plays a pivotal role in the emergence of tolerance, persistence, and resistance toward biocides in microbial populations (1, 2). Also, microbial populations show highly complex interactions, e.g., in the competition for nutrients or in the colonization of new habitats (3). In recent years, newly developed tools for single-cell analysis have greatly extended our understanding of biological variation in microbial populations and its underlying mechanisms (4). These tools allow genome sequencing (5) or follow transcription as well as protein synthesis on the single-cell level (6). Since these techniques give a much higher resolution when observing processes in given cell populations, they permit insight into inter-and intracellular processes and the underlying mechanisms. However, when it comes to highthroughput measurements of small molecules, very few methods are currently known (7).The singular qualities of individual cells can only be fully appreciated within the context of the population. Therefore, one of the most important features for single-cell methods to be useful in biological applications is high-throughput capability. One of the most successful high-throughput approaches to characterize heterogeneities in microbial populations is flow cytometry (8). It has the benefits of high sensitivity and a high linear dynamic range of fluorescence tagging and optical detection. However, the method is strongly limited in parallelization, since excitation and emission bands overlap. Mass cytometry, on the other hand, which is a new approach that can be coupled to flow cytometry, uses antibodies tagged with rare earth metals (9). With mass spectrometric detection, over 40 features can be meas...

There is increasing evidence that rapid phenotypic evolution can strongly influence population dynamics, but how are such eco-evolutionary dynamics influenced by the source of trait variation (i.e., genetic variation or phenotypic plasticity)? To investigate this, we used rotifer-algae microcosm experiments to test how the phenotypic and genetic composition of prey populations affect predator-prey population dynamics. We chose four genetically distinct strains of the green alga Chlamydomonas reinhardtii that varied in their growth rate, standing levels of defense, and inducible defense. To additionally test for strain specificity of plasticity responses, we quantified protein expression of each strain in the presence and absence of rotifer predators (Brachionus calyciflorus). We then tested how different strain combinations influenced the outcome of pairwise competition trials with and without rotifer predation. We tracked individual strain frequencies using quantitative polymerase chain reaction (qPCR), and compared the observed dynamics to a suite of ecoevolutionary models of varying complexity. We found that variation in trade-offs between growth and defense between algal strains strongly influenced the outcome of competition and the overall predator-prey dynamics. Our purely ecological model of the observed dynamics, which allowed for the presence of phenotypic plasticity but no trait variation between strains, never outperformed any of our eco-evolutionary models in which strains could have different trait values. Our best fitting eco-evolutionary model allowed strains to differ in an inducible defense trait. Overall, our results provide some of the first experimental evidence that variation in phenotypically plastic responses among prey genotypes can be an important component of eco-evolutionary dynamics in a predator-prey system.

Phenotypic variation is vital for microbial populations to survive environmental perturbations. Both genetic and non-genetic factors contribute to an organism's phenotypic variation and therefore its fitness. To investigate the correlation between genetic diversity and phenotypic variation, we applied our recently developed mass spectrometry method that allows for the simultaneous measurement of more than 25 different lipids and pigments with high throughput in the unicellular microalga Chlamydomonas reinhardtii. We monitored the impact of nitrogen limitation on a genetically diverse wild-type strain CC-1690 and two isoclonal isolates from CC-1690 named ANC3 and ANC5. Measuring molecular composition of thousands of single cells at different time points of the experiment allowed us to capture a dynamic picture of the phenotypic composition and adaptation of the populations over time. Although the genetically diverse population maintained phenotypic variation over the whole time course of the experiment, the isoclonal cultures showed higher synchronicity in their phenotypic response. Furthermore, the genetically diverse population showed equal or greater phenotypic variation over the whole time range in multidimensional trait space compared with isoclonal populations. However, along individual trait axes non-genetic variance was higher in isoclonal populations.

We demonstrate a new approach for the site-specific identification and characterization of protein N-glycosylation. It is based on a nano-liquid chromatography microarray-matrix assisted laser desorption/ionization-MS platform, which employs droplet microfluidics for onplate nanoliter reactions. A chromatographic separation of a proteolytic digest is deposited at a high frequency on the microarray. In this way, a short separation run is archived into thousands of nanoliter reaction cavities, and chromatographic peaks are spread over multiple array spots. After fractionation, each other spot is treated with PNGaseF to generate two correlated traces within one run, one with treated spots where glycans are enzymatically released from the peptides, and one containing the intact glycopeptides. Mining for distinct glycosites is performed by searching for the predicted deglycosylated peptides in the treated trace. An identified peptide then leads directly to the position of the "intact" glycopeptide clusters, which are located in the adjacent spots. Furthermore, the deglycosylated peptide can be sequenced efficiently in a simple collision-induced dissociation-MS experiment. We applied the microarray approach to a detailed site-specific glycosylation analysis of human serum IgM. By scanning the treated spots with low-resolution matrix assisted laser desorption/ionization-time-offlight-MS, we observed all five deglycosylated peptides, including the one originating from the secretory chain. A detailed glycopeptide characterization was then accomplished on the adjacent, untreated spots with high mass resolution and high mass accuracy using a matrix assisted laser desorption ionization-Fourier transform-MS. We present the first detailed and comprehensive mass spectrometric analysis on the glycopeptide level for human polyclonal IgM with high mass accuracy. Besides complex type glycans on Asn 395, 332, 171, and on the J chain, we observed oligomannosidic glycans on Asn 563, Asn 402 and minor amounts of oligomannosidic glycans on the glycosite Asn 171. Furthermore, hybrid type glycans were found on Asn 402, Asn 171 and in traces Asn 332. Molecular & Cellular