Proper sample preparation protocols represent a critical step for liquid chromatography-mass spectrometry (LC-MS)-based proteomic study designs and influence the speed, performance and automation of high-throughput data acquisition. The main objective of this study was to compare two commercial solid-phase extraction (SPE)-based sample preparation protocols (comprising SOLAµTM HRP SPE spin plates from Thermo Fisher Scientific and ZIPTIP® C18 pipette tips from Merck Millipore) for analytical performance, reproducibility, and analysis speed. The house swine represents a promising animal model for studying human eye diseases including glaucoma and provides excellent requirements for the qualitative and quantitative MS-based comparison in terms of ocular proteomics. In total six technical replicates of two protein fractions [extracted with 0.1% dodecyl-ß-maltoside (DDM) or 1% trifluoroacetic acid (TFA)] of porcine retinal tissues were subjected to in-gel trypsin digestion and purified with both SPE-based workflows (N = 3) prior to LC-MS analysis. On average, 550 ± 70 proteins (1512 ± 199 peptides) and 305 ± 48 proteins (806 ± 144 peptides) were identified from DDM and TFA protein fractions, respectively, after ZIPTIP® C18 purification, and SOLAµTM workflow resulted in the detection of 513 ± 55 proteins (1347 ± 180 peptides) and 300 ± 33 proteins (722 ± 87 peptides), respectively (FDR < 1%). Venn diagram analysis revealed an average overlap of 65 ± 2% (DDM fraction) and 69 ± 4% (TFA fraction) in protein identifications between both SPE-based methods. Quantitative analysis of 25 glaucoma-related protein markers also showed no significant differences (P > 0.05) regarding protein recovery between both SPE methods. However, only glaucoma-associated marker MECP2 showed a significant (P = 0.02) higher abundance in ZIPTIP®-purified replicates in comparison to SOLAµTM-treated study samples. Nevertheless, this result was not confirmed in the verification experiment using in-gel trypsin digestion of recombinant MECP2 (P = 0.24). In conclusion, both SPE-based purification methods worked equally well in terms of analytical performance and reproducibility, whereas the analysis speed and the semi-automation of the SOLAµTM spin plates workflow is much more convenient in comparison to the ZIPTIP® C18 method.

Proper sample preparation protocols represent a critical step for liquid chromatography-mass spectrometry (LC-MS)-based proteomic study designs and influence the speed, performance and automation of high-throughput data acquisition. The main objective of this study was to compare two commercial solid-phase extraction (SPE)-based sample preparation protocols (comprising SOLAµ TM HRP SPE spin plates from Thermo Fisher Scientific and ZIPTIP ® C18 pipette tips from Merck Millipore) for analytical performance, reproducibility, and analysis speed. The house swine represents a promising animal model for studying human eye diseases including glaucoma and provides excellent requirements for the qualitative and quantitative MS-based comparison in terms of ocular proteomics. In total six technical replicates of two protein fractions [extracted with 0.1% dodecyl-ß-maltoside (DDM) or 1% trifluoroacetic acid (TFA)] of porcine retinal tissues were subjected to in-gel trypsin digestion and purified with both SPE-based workflows (N = 3) prior to LC-MS analysis. On average, 550 ± 70 proteins (1512 ± 199 peptides) and 305 ± 48 proteins (806 ± 144 peptides) were identified from DDM and TFA protein fractions, respectively, after ZIPTIP ® C18 purification, and SOLAµ TM workflow resulted in the detection of 513 ± 55 proteins (1347 ± 180 peptides) and 300 ± 33 proteins (722 ± 87 peptides), respectively (FDR < 1%). Venn diagram analysis revealed an average overlap of 65 ± 2% (DDM fraction) and 69 ± 4% (TFA fraction) in protein identifications between both SPE-based methods. Quantitative analysis of 25 glaucoma-related protein markers also showed no significant differences (P > 0.05) regarding protein recovery between both SPE methods. However, only glaucoma-associated marker MECP2 showed a significant (P = 0.02) higher abundance in ZIPTIP ®-purified replicates in comparison to SOLAµ TM-treated study samples. Nevertheless, this result was not confirmed in the verification experiment using in-gel trypsin digestion of recombinant MECP2 (P = 0.24). In conclusion, both SPE-based purification methods worked equally well in terms of analytical performance and reproducibility, whereas the analysis speed and the semi-automation of the SOLAµ TM spin plates workflow is much more convenient in comparison to the ZIPTIP ® C18 method.

No abstract

&lt;p&gt;Speleothems are secondary mineral deposits found in caves. They can grow continuously over 1,000-10,000 years and the &lt;sup&gt;230&lt;/sup&gt;Th/U method allows accurate dating back to 500,000 years.[1] Stable conditions in caves preserve organic matter, making speleothems highly valuable climate archives. The high interest in expanding the range of organic proxies in speleothems requires highly sensitive analytical techniques. Novel trace analysis methods for lignin and levoglucosan in speleothems were established according to principles of &quot;Green Chemistry&quot; [2] and applied to flowstone samples from different caves in New Zealand during the Holocene.&lt;/p&gt;&lt;p&gt;Lignin is the second most abundant biopolymer after cellulose. It consists of three monomers, which are included into the polymer in different ratios, depending on the type of vegetation. It is found in speleothems and quantification in timely consecutive layers allows drawing conclusions on changing types and amount of vegetations above the caves, which are influenced by climate conditions like temperature and rainfall.[3] To analyse the monomeric composition, lignin has to be degraded by an alkaline oxidation. Thereby the monomers are oxidized into lignin oxidation products which are then analysed by uHPLC-ESI-HRMS. To date, lignin degradation was conducted using Cu(II)O as a catalyst, which was replaced by CuSO&lt;sub&gt;4&lt;/sub&gt;, eliminating the solid, toxic Cu(II)O waste, and highly reducing the amount of artefacts and used chemicals during sample preparation. The new method was successfully applied to the flowstone samples but posed further questions on the transport of lignin through the soil into the speleothem.[4],[5]&amp;#160; &amp;#160;&lt;/p&gt;&lt;p&gt;The other proxy of interest was levoglucosan, an anhydrosugar formed by cellulose combustion. For temperature studies in speleothems carbon isotopes are used which can be influenced by e.g. fire events. Therefore, it is necessary to introduce a proxy, which prevents falsely positive or negative temperature trends. Extraction of levoglucosan was conducted using graphitized carbon black and chromatographic separation by a hydrophilic interaction liquid chromatography, using a post-column flow to increase the ionization efficiency in the ESI ion source. Levoglucosan analysis was introduced into the existing workflow, without interfering with lignin analysis, and thereby a multi-proxy approach was developed. This work showed that levoglucosan is present in speleothems in quantifiable amounts. It was detected in two of the study sites, showing no correlation to lignin. A plant-based origin of levoglucosan was ruled out, suggesting a fire-related entry into the speleothem.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;[1] Baker, A., et al. (2008). International Journal of Speleology, 37 (3), 193-206; [2] Anastas, P., Eghbali, N. (2010), Chemical Society Reviews, 39, 301-312; [3] Hedges, J., Mann, D. (1979). Geochimica et Cosmochimica Acta, 43 (11), 1803-1807; [4] Heidke, I., Scholz, D., Hoffmann, T. (2018). Biogeosciences, 15 (19), 5831-5845; [5] Yan, G., Kaiser, K. (2018). Analytical Chemistry , 90 (15), 9289-9295&lt;/p&gt;

&lt;p&gt;Secondary mineral deposits in caves like stalagmites, stalactites, or flowstones are valuable paleoclimate archives. Advantages of organic trace analysis in such deposits are stable conditions in a cave, protecting compounds from external influences, as well as the possibility to precisely date samples up to 600,000 years using the uranium/thorium method.[1]&lt;/p&gt;&lt;p&gt;Lignin, a biopolymer, is one of the main constituents of higher plants and consists of three monomeric units: sinapyl-, coniferyl-, and coumaryl alcohol. Lignin can be degraded into its monomeric units by alkaline CuSO&lt;sub&gt;4&lt;/sub&gt;-oxidation. The oxidized monomer units can be analysed by UHPLC-ESI-HRMS with limits of quantification in the ng/g range. By determination of the ratios among different oxidation products in a speleothem, conclusions can be drawn on the type of vegetation above the cave. [2,3]&lt;/p&gt;&lt;p&gt;Levoglucosan, an anhydrosugar, naturally only originates from the combustion of cellulose and can thus be used as a biomass burning marker. Analysis of levoglucosan in sediments shows good correlation with traditional burning markers like black charcoal. [4] Mannosan and galactosan, stereoisomers of levoglucosan, are formed during the combustion of hemicellulose. Literature suggests that the ratio of levoglucosan to its isomers rather than absolute levoglucosan concentrations should be considered when characterizing burning events. [5] To date, no data on levoglucosan or its isomers in speleothems is published.&lt;/p&gt;&lt;p&gt;As the anhydrosugars are highly polar molecules, extraction and analysis with traditional reversed phase systems proved difficult. An optimized sample preparation to access both lignin and levoglucosan in speleothems is presented. Furthermore, a HILIC-UHPLC-ESI-HRMS method was developed to analyze the lignin oxidation products (LOPs) and anhydrosugars.&lt;/p&gt;&lt;p&gt;The methods were applied to a flowstone from a cave of the Dolomites in Southern Tyrol.&lt;/p&gt;&lt;p&gt;[1] D. Scholz, D. Hoffmann, Quat. Sci. J. 57 (2008) 52&amp;#8211;76 [2] C.N. Jex et al. Quat. Sci. Rev. 87 (2014) 46&amp;#8211;59. [3] G. Yan, K. Kaiser, Anal. Chem. 90 (2018) 9289&amp;#8211;9295. [4] V. O. Elias et al. Geochim. et Cosmochim. Acta 65 (2001) 267-272. [5] D. Fabbri et al. Atmos. Env. 43 (2009) 2286&amp;#8211;2295&lt;/p&gt;