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Cell Reports, Volume 2, Issue 2, 419-431, 16 August 2012
Proteomic Analysis of Lysine Acetylation Sites in Rat Tissues Reveals Organ Specificity and Subcellular Patterns
Alicia Lundby1, 2, 3, Kasper Lage1, 3, 4, 5, Brian T. Weinert1, Dorte B. Bekker-Jensen1, Anna Secher1, 6, Tine Skovgaard1, Christian D. Kelstrup1, Anatoliy Dmytriyev1, Chunaram Choudhary1, Carsten Lundby7 and Jesper V. Olsen1, ,
1 Novo Nordisk Foundation Center for Protein Research, Department for Proteomics, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen N, Denmark
2 The Danish National Research Foundation Centre for Cardiac Arrhythmia, 2200 Copenhagen N, Denmark
3 The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
4 Pediatric Surgical Research Laboratory, Massachusetts General Hospital, Boston, MA 02114, USA
5 Department of Surgery, Harvard Medical School, Boston, MA 02115, USA
6 Novo Nordisk A/S, Novo Nordisk Park, 2760 Måløv, Denmark
7 Zürich Centre for Integrative Human Physiology, Department of Physiology, University of Zürich, 8057 Zürich, Switzerland
Graphical Abstract
► Identification of 15,474 lysine acetylation sites on 4,541 proteins in tissues ► Lysine acetylation sequence motifs differ between subcellular compartments ► Acetylation of lysine residues can switch off enzymatic activity ► The subcellular distribution of acetylation differs from phosphorylation
- Lysine acetylation is a major posttranslational modification involved in a broad array of physiological functions. Here, we provide an organ-wide map of lysine acetylation sites from 16 rat tissues analyzed by high-resolution tandem mass spectrometry. We quantify 15,474 modification sites on 4,541 proteins and provide the data set as a web-based database. We demonstrate that lysine acetylation displays site-specific sequence motifs that diverge between cellular compartments, with a significant fraction of nuclear sites conforming to the consensus motifs G-AcK and AcK-P. Our data set reveals that the subcellular acetylation distribution is tissue-type dependent and that acetylation targets tissue-specific pathways involved in fundamental physiological processes. We compare lysine acetylation patterns for rat as well as human skeletal muscle biopsies and demonstrate its general involvement in muscle contraction. Furthermore, we illustrate that acetylation of fructose-bisphosphate aldolase and glycerol-3-phosphate dehydrogenase serves as a cellular mechanism to switch off enzymatic activity.
Lysine acetylation is a reversible posttranslational modification involved in multiple cellular processes, where an acetyl group is transferred to the epsilon-amino group of an internal lysine residue of a protein. The importance of lysine acetylation is well appreciated in the context of nuclear histone modifications (Strahl and Allis, 2000), but the regulatory implications of the modification extend beyond gene regulation. Changes in cellular lysine acetylation status can alter metabolic enzyme activity and provide a mechanism for the cell to adapt to metabolic changes (Rodgers et al., 2008; Wang et al., 2010; Zhao et al., 2010), for instance by regulating key enzymes of the tricarboxylic acid cycle, the urea cycle, and fatty acid oxidation (Ahn et al., 2008; Hirschey et al., 2010; Kim et al., 2006; Nakagawa et al., 2009). The physiological importance of dynamic acetylation as a regulatory mechanism of metabolism has been highlighted in recent studies of the liver (Zhao et al., 2010), where the distribution of lysine acetylation sites changes under conditions of either acute fasting (Yang et al., 2011) or caloric restriction (Schwer et al., 2009). An overlap of 70% has been reported for acetylation sites identified from mouse and human liver tissues, whereas the overlap with data from cell lines was only 14% (Zhao et al., 2010). Because lysine acetylation sites are evolutionarily conserved (Wang et al., 2010; Weinert et al., 2011), this suggests that acetylation patterns vary depending on the particular cellular functions to be performed. To explore physiologically relevant lysine acetylation substrates, it is pivotal to have knowledge of which proteins are acetylated in vivo and to know the tissue distribution of the modified sites. The value of creating extensive, tissue-specific maps of protein lysine acetylation sites is further underscored by the significant role of posttranslational modifications in the evolution and phenotypic composition of vertebrates, as indicated by the significant selective pressure gene regulatory elements near posttranslational-modifying enzymes have come under in placental animals (Lowe et al., 2011). Here, we combined an efficient method for protein extraction from tissue samples with lysine-acetylated peptide immunoprecipitation and high-accuracy tandem mass spectrometric (MS/MS) measurements, which allowed us to generate an atlas of lysine acetylation sites in 16 different rat tissues. Our acetylome data set expands the current number of lysine acetylation sites by 4-fold and the number of acetylated proteins by 2-fold (Choudhary et al., 2009; Wang et al., 2010; Weinert et al., 2011). We achieved this by improving the antibody-based enrichment protocol significantly, such that 40% of all tandem mass spectra identify lysine-acetylated peptides. We map ∼3,000–6,000 acetylation sites in most tissues by analyzing just three strong cation exchange (SCX) fractions with single 3 hr tandem mass spectrometric runs. We provide tissue-specific evidence that lysine acetylation is comparable to phosphorylation in cellular prevalence. Our data set highlights tissue-specific pathways involving lysine-acetylated proteins, which stresses the importance of mapping protein modifications in the physiologically relevant tissue. Among the findings, we observe that almost all proteins involved in striated muscle contraction are acetylated, and we confirm this finding in human skeletal muscle biopsies. Not only do we find that specific proteins and sites are differentially acetylated across tissues, we also show that the distribution of lysine-acetylated proteins in subcellular compartments is tissue specific. Our large data set allows us to delineate lysine acetylation sequence motifs, and contrary to what has been previously known, we show that there are subcellular compartment-specific sequence motifs. We provide easy access to all data via a searchable online database.
Identification of 15,474 Lysine Acetylation Sites from 4,541 Proteins
A total of 16 different organs and tissues were dissected from Sprague-Dawley albino rats (SPRD; Taconic, Denmark) to map lysine acetylation sites of proteins across tissues. The tissues were brain, heart, muscle, lung, kidney, liver, stomach, pancreas, spleen, thymus, intestine, skin, testis, testis fat, perirenal fat, and brown fat (Figure 1A). Organs from five rats were pooled to account for biological variation. Protein extracts were digested in solution in a urea buffer with sequential steps of Lys-C and trypsin incubations. The resulting peptides were desalted and enriched for lysine-acetylated peptides by immunoprecipitation followed by fractionation by microscale SCX chromatography (Weinert et al., 2011). The three resulting SCX fractions were analyzed by 3 hr nanoflow liquid chromatography tandem mass spectrometry (LC-MS/MS) gradients on a LTQ-Orbitrap Velos mass spectrometer (Olsen et al., 2009) with all tandem mass spectra recorded in the orbitrap analyzer at high resolution using the higher-energy collisional dissociation (HCD) technology (Olsen et al., 2007). Peptide sequences were identified by Mascot, and lysine-acetylated proteins were quantified using the MaxQuant software suite's label-free algorithm based on peptide-extracted ion chromatograms (XICs). In total 1,060,605 high-resolution HCD-MS/MS events were collected resulting in 265,034 peptide-spectrum matches at a false discovery rate below 0.01. A total of 105,904 HCD spectra identified lysine-acetylated peptides, which corresponds to 40% of all MS/MS identifications. The data set covered 62,553 unique modification-specific peptides, of which 19,965 were lysine acetylated, matching to 15,474 lysine acetylation sites from 4,541 proteins.
To facilitate the ease of searching the data set for modifications on particular proteins of interest, we have created an online database, the CPR PTM Resource, where we have recorded the entire tissue-specific lysine acetylation data set. At the CPR PTM Resource, information on the tissue distribution of posttranslational modifications on a given protein is provided along with topological protein information imported from other sources. To further allow for easy meta-analysis of the data set for the scientific community, we provide 60 raw files as well as 22,789 annotated lysine-acetylated peptide HCD-MS/MS spectra as a resource for download via TRANCHE (see Extended Experimental Procedures). Tables with all modification-specific peptides (Table S1. All Modified Peptides Identified), identified lysine acetylation sites (Table S2. All Quantified Lysine Acetylation Sites), and proteins (Table S3. All Quantified Lysine-Acetylated Proteins) are also provided both in the Extended Experimental Procedures and at the CPR PTM Resource website. Evaluation of the high-quality mass spectrometry (MS) and MS/MS data is shown in Figure S1. Figure S2 illustrates our successful enrichments of lysine-acetylated peptides and peptide fractionation, which were instrumental factors, for allowing us to expand the current number of lysine acetylation sites by 4-fold.
Distribution of Lysine Acetylation Sites across Tissues
For individual tissues there is excellent technical reproducibility of the entire experimental workflow (Figure 1B). Figure 1B summarizes three technical replicates for two different tissue types: liver, which is known to have high abundance of lysine-acetylated proteins; and skeletal muscle, which has not previously been studied in the context of lysine acetylation. The correlation analysis of lysine-acetylated peptide MS signal intensities between technical replications prepared from the same tissue reveals Pearson coefficients < R > = 0.95 for liver and < R > = 0.91 for muscle. Importantly, there is poor correlation between muscle and liver tissues: < R > = 0.37. The high reproducibility of the MS data collected from a given tissue enables us to perform relative label-free quantification of lysine acetylation sites between tissues. We evaluated the tissue distribution of lysine-acetylated proteins by hierarchical clustering analysis of normalized acetylated protein intensities derived from summed MS signal intensities from each tissue (Figure 2A). The acetylated proteins are color coded according to their normalized intensities, which are a measure for their relative abundances in each tissue (de Godoy et al., 2008; Malmström et al., 2009). Protein acetylation patterns vary greatly across tissues, but functionally related tissues cluster together, as for instance the major energy-consuming tissues (heart, muscle, and brown fat) and organs containing lymphoid tissue (lung, spleen, thymus, pancreas, and intestine). Because we identify most high-abundant proteins to be acetylated, this clustering profile is likely partly due to similarities in protein expression patterns, in addition to similarities in acetylation patterns. For most tissues we identify on the order of 1,000 lysine-acetylated proteins, but a few tissues display significantly more acetylated proteins. For example in kidney there are 2,061 acetylated proteins containing 6,283 modified residues (Figure 2A). To explore the differences underlying the tissue-specific patterns of acetylated proteins in each tissue cluster, we performed gene ontology (GO) (Ashburner et al., 2000) and pathway (Reactome) (Croft et al., 2011) enrichment analyses. Testing which pathways are enriched in the entire data set of 4,541 acetylated proteins identifies the main pathways previously recognized to be regulated by lysine acetylation such as gene expression, protein metabolism, the citric acid (TCA) cycle, and apoptosis (Figure 2B). However, focusing on the acetylated proteins that are specifically enriched for each of the tissue clusters identifies tissue-specific pathways, which for the most part have not previously been shown to involve lysine acetylation. In general the tissue-specific pathways correlate well with the known physiological roles of the tissues, which possibly reflect that the high-abundant acetylated proteins are expressed in a tissue-specific manner. For instance the cluster with the major energy-consuming tissues is significantly enriched for proteins involved in striated muscle contraction as well as respiratory electron transport. Conversely, the cluster with organs containing lymphoid tissue is significantly enriched for proteins involved in various aspects of transcription and translation. The acetylated proteins that are more abundant in the brain than in other tissues are primarily involved in neuronal signal transmission, whereas the specific acetylated proteins of the stomach, liver, and kidney are enriched for proteins involved in metabolism of amino acids and vitamins (Figure 2B). Thus, lysine acetylation is targeting tissue-specific biological processes, and it is involved in diverse cellular functions across tissues.
As a starting point for deciphering tissue-specific molecular networks of lysine-acetylated proteins, we generated protein-protein interaction networks based on proteins that are acetylated in a tissue-specific manner. We identified interaction partners using the InWeb database of quality-controlled protein-protein interactions (Lage et al., 2007, Lage et al., 2008, Lage et al., 2010) and applied a network-building algorithm to build protein-interaction networks with quality thresholds optimized by permutation tests (Bergholdt et al., 2007; Lage et al., 2010). Five of the protein-interaction networks of tissue-specific acetylated proteins interact significantly (0.0261 ≤ adj. p ≤ 0.0467, adjusted for multiple testing using a Bonferroni correction), indicating that proteins with tissue-specific acetylation patterns have a strong tendency to directly interact or are part of connected tissue-specific pathways. The high connectivity in interaction space of acetylated proteins is clearly illustrated in the network based on proteins specifically acetylated in brain (Figure S3). We provide all networks in flat file and Cytoscape session formats as a resource for the community through the CPR PTM Resource web page.
Lysine Acetylation in Rat and Human Striated Muscle Contraction
To investigate one of the tissue-specific roles of lysine acetylation further, we decided to focus on striated muscle contraction. More than 80% of the proteins involved in striated muscle contraction are acetylated (Figure 3A). To ensure that this finding is of general physiological relevance, we performed similar experiments on human skeletal muscle biopsies from three age-matched athletes. From these samples we assess the biological variation of lysine acetylation site abundance. Pearson correlation coefficients range from 0.81 to 0.90 (Figure 3B), thus indicating that it will be possible to perform quantitative lysine acetylation analyses of human samples, and not only from inbred animals. From the human skeletal muscle samples, we identify a total of 941 acetylated proteins containing 2,811 acetylation sites (Table S4. Human Skeletal Muscle Lysine-Acetylated Peptides). The lysine acetylation sites identified in human skeletal muscle confirm the acetylation pattern of proteins involved in muscle contraction. In muscle the cellular compartment with the highest abundance of lysine acetylation is the mitochondria, and in rat as well as in human muscle samples, we identify lysine acetylation sites on proteins involved in all enzymatic steps of the major mitochondrial metabolic pathways (Figure 3C). Thus, proteins involved in muscle contraction are hyperacetylated as are the metabolic enzymes generating ATP, which collectively points to an important role of lysine acetylation in skeletal muscle physiology.
Functional Analysis of Site-Specific Acetylation Sites on Glycolytic Enzymes
In accordance with the increasing evidence that supports lysine acetylation as a major cellular mechanism that regulates glucose metabolism (Wang et al., 2010; Yang et al., 2011; Zhao et al., 2010), we identify multiple acetylation sites on enzymes involved in the glycerol synthesis pathway. Interestingly, there is a tissue-specific distribution of sites between the enzymes in human skeletal muscle, rat brain and rat liver (Figure 4A). We identified all three genetically distinct and tissue-specific isozymes of fructose-bisphosphate aldolase known in mammals, with specific acetylated peptides from ALDOA in human muscle, ALDOB in liver, and ALDOC in brain. Aldolase deficiency in humans leads to fructose intolerance, and two-thirds of patients suffering from hereditary fructose intolerance have a common missense mutation in the ALDOB gene resulting in an amino acid substitution A150P (Davit-Spraul et al., 2008). This mutation is in close proximity of lysine 147 (K147), which we find to be abundantly acetylated in intestine, stomach, kidney, and liver (Figure 4B). To estimate the occupancy of this lysine acetylation site, we modified a method we previously developed to calculate phosphorylation site occupancy from SILAC-labeled samples (Olsen et al., 2010). Our approach relies on the label-free quantification measurements and uses the information contained in the normalized peptide intensities for a given acetylated peptide and its corresponding nonacetylated peptide combined with relative iBAQ estimated protein abundances between tissues (Schwanhäusser et al., 2011). Our occupancy calculations show that K147 is acetylated on ∼33% of the ALDOB proteins in the liver and on ∼20% of the proteins in the stomach, thus indicating a potential physiological role. K147 as well as the surrounding amino acids is highly conserved from vertebrates to probacteria (Figure 4C). Because K147 furthermore is important for substrate binding (St-Jean et al., 2009), we decided to investigate functional effects of acetylation of this residue on ALDOB enzymatic activity. We expressed full-length human ALDOB in a wild-type and K147Q acetylation mimetic mutant and measured the enzymatic activity of the purified proteins. Wild-type ALDOB efficiently converts fructose-1,6-bisphosphate to glyceraldehyde-3-phosphate and dihydroxyacetone phosphate at a rate of 0.34 ± 0.01 μmol/min/mg. Strikingly, the K147Q mutation appears to abolish the enzymatic activity of ALDOB because this mutant shows no detectable activity in our assay (Figure 4D). Hence, the wild-type enzyme is at least three orders of magnitude more active than the K147Q mutant. This finding highlights that site-specific acetylation can function as an efficient cellular mechanism to switch off the enzymatic activity of important regulatory proteins. To investigate if this regulatory switch is restricted to aldolases, or if lysine acetylation of substrate binding sites is a general mechanism to inhibit enzymes in the glycogen synthesis pathway, we tested the function of an equivalent lysine acetylation site we identified on glycerol-3-phosphate dehydrogenase (GPD1). K120 on GPD1 is predicted to serve as a substrate binding site (Ou et al., 2006), and we identified this residue to be acetylated. Analogous to the functional test of ALDOB, we purified wild-type GPD1 as well as the K120Q mutant and assayed their enzymatic activity (Figure 4E). The activity of wild-type enzyme was measured to 4.4 ± 0.4 μmol/min/mg, whereas the acetylation mimicking mutated enzyme has activity levels below the detection limit. The difference in activity between the wild-type and mutant GPD1 is more than three orders of magnitude, thus again providing evidence for lysine acetylation as a mechanism for switching off enzymatic activity.
Cellular Compartment Distribution of Lysine-Acetylated Proteins
To investigate the distribution of acetylated proteins across cellular compartments, we evaluated the proteins according to their GO cellular compartment annotations. The majority of acetylated proteins reside in either the cytoplasm or the nucleus, which each contain ∼30% of all the acetylated proteins. The mitochondria and the plasma membrane both account for ∼15% of modified proteins, and the endoplasmic reticulum or Golgi apparatus (ER/Golgi) as well as the extracellular space harbor ∼5% (Figure 5A). Two tissue atlases of phosphoproteins have been published, one for mouse and one for rat (Huttlin et al., 2010; Lundby et al., 2012), so to compare the distribution of phosphoproteins to that of acetylated proteins, we exploited the rat data set we have generated. Interestingly, the subcellular distribution of acetylated proteins is markedly different from the distribution of phosphorylated proteins (Figure S4). The fraction of modified proteins residing in the mitochondria is more than 3-fold higher for lysine-acetylated proteins compared to phosphorylated proteins. On the contrary the fraction of protein substrates localized to the plasma membrane is more than 2-fold higher for phosphorylation compared to acetylation. However, the subcellular distribution of lysine-acetylated proteins is tissue dependent and possibly reflects the distribution of unmodified proteins. For example the brain accounts for the largest fraction of acetylated membrane proteins, which explains why pathway enrichment analysis of all acetylated plasma membrane proteins emphasizes neurophysiological functions (Figure 5B). Alike, the three adipose tissues are abundant in acetylated proteins associated with the extracellular space, which is likely associated to adipose tissues being major endocrine organs (Kratchmarova et al., 2002; Saltiel, 2001). Organs containing lymphoid tissue (spleen, thymus, pancreas, lung, and intestine) contain a higher fraction of acetylated nuclear proteins than any of the other tissues, and these nuclear proteins are significantly enriched for sequence-specific DNA binding transcription factor activity (p = 9 × 10−4). Focusing on the proteins underlying this enrichment, we discover that lysine acetylation is significantly more abundant on 82 of 129 modified transcription factors in these tissues (Table S5. All Identified Transcription Factors with Lysine Acetylation Sites). This observation likely reflects that lymphoid-containing tissues have high self-renewal rates (Pellettieri and Sánchez Alvarado, 2007) and, therefore, require high transcriptional activity.
At the global level we identify an average of 2.8 lysine acetylation sites per protein per tissue (Figure 2A), but as evident from Figure 5A, this number greatly varies between cellular compartments. Mitochondrial proteins exhibit the greatest number of acetylation sites with an average of 5.6 sites per protein. This may explain why many previous studies primarily identified acetylation sites from mitochondrial proteins, although this is not the compartment with the greatest number of acetylated proteins. To test if the tendency toward multiacetylated proteins in the mitochondria is biased by protein abundance, we estimated the relative protein abundance for all proteins using the iBAQ method. Analyzing the number of acetylation sites per protein as function of protein abundance revealed that mitochondrial proteins have significantly more modified sites at all protein abundance levels (Figure S5). The tissues with the largest fraction of acetylated mitochondrial proteins are muscle, heart, and brown fat. More than 35% of all identified acetylation sites in these tissues are mitochondrial, with a significant overrepresentation of proteins involved in the electron transport chain (p = 7 × 10−3). Thus, the result likely reflects the high-energy demand and oxidative capacity of these particular tissues.
Lysine Acetylation Sequence Motifs Are Specific for Cellular Compartments
We explored our data set for lysine acetylation site-specific sequence motifs by analyzing the 12 residues flanking the modified site for overrepresentation of specific amino acids relative to the proteome background distribution. Analysis of all identified acetylation sites reveals general preferences for specific amino acid residues at particular positions surrounding the acetylated lysines (Figure 6A). As also previously reported (Weinert et al., 2011), we find that lysine acetylations preferentially occur in lysine-rich regions, with a tendency toward negatively charged residues in the immediate surroundings of the modified site. Position-specific preferences include glycine residues at amino acid position −1 relative to the acetylated residue, proline/phenylalanine/tyrosine residues at amino acid position +1, and valine/isoleucine residues at amino acid position +2. We next investigated if these sequence preferences are similar across all cellular compartments. Interestingly, the global sequence motif map we find appears to be a merged picture of compartment-specific motifs (Figure S6). To visualize compartment-specific sequence motifs, we analyzed all lysine acetylation sites from proteins localized to a particular subcellular compartment relative to the rat protein database using iceLogo (Colaert et al., 2009) (Figure 6B). This analysis reveals that the sequence motifs indeed differ for subcellular compartments. The preference for lysine-rich regions is general to all compartments, but on cytoplasmic proteins there is a clear preference for glutamate residues at all positions in the vicinity of the acetylation site. Mitochondrial proteins have a preference for negatively charged residues in the immediate vicinity of the acetylation site, but they additionally show a strong preference for hydrophobic residues (V/I/L/F) at position +2. Proteins that reside in either ER/Golgi also have the general preference for negatively charged residues but further favor hydrophobic residues (I/L) at positions −1 and −2. The most distinct sequence motif is evident on nuclear proteins, where there is a strong preference for glycine residues in position −1 and proline residues in position +1. Because this nuclear sequence motif differs substantially from the previously reported motif for lysine acetylation of histones (K-X-X-X-AcK-X-X-X-K) (Kim et al., 2006), we next analyzed sites identified from histones separately. This analysis indeed confirms that the preferred sequence motif for histones differs from other nuclear proteins and that it conforms to the known motif with lysines at positions ±4 (Figure 6C). Another group of nuclear proteins of particular interest is transcription factors, and because we have identified a total of 388 acetylation sites on transcription factors, we next tested if these contain a particular sequence motif. We find that transcription factors display a similar motif as the other nuclear proteins (G-AcK-P), which thus differs for the one found for histones (Figure 6C). The identified compartment-specific sequence motifs are summarized in Figure 6D.
The importance of tissue-specific mapping of posttranslational modifications of proteins is underscored by the substantial differences we find for lysine acetylation patterns across tissues. Our data set provides a rich resource of candidates for hypothesis generation and subsequent mechanism-focused studies to elucidate the tissue-specific protein networks that are controlled by regulatory site-specific lysine acetylation. In addition the data set provides evidence that site-specific lysine-acetylated proteins are involved in multiple physiological functions with which the modification has not previously been associated. For example we show that almost all proteins involved in muscle contraction are acetylated both in rat striated muscle as well as in human skeletal muscle. In particular we find that multiple enzymes involved in ATP generation are hyperacetylated in skeletal muscle mitochondria, for many of which it is known that the enzymatic activity of their bacterial orthologs is regulated by lysine acetylation (Wang et al., 2010). Because acetylation of muscle LIM protein is moreover known to enhance calcium sensitivity of myofilaments in cardiomyocytes (Gupta et al., 2008), our findings strongly imply that muscle-contractile proteins are regulated by lysine acetylation in addition to the well-established role of phosphorylation in muscle contraction. This notion is further supported by our demonstration that site-specific acetylation of two glycolytic enzymes, ALDOB and GPD1, serves as a regulatory mechanism for switching off their enzymatic activity. It is intriguing to speculate that lysine acetylation of substrate binding sites may be a general cellular mechanism to control metabolic enzyme activity in a manner analogous to phosphorylation-dependent regulation of protein kinases and signal transducers. In contrast to the activating effects of phosphorylation, acetylation could function to switch off enzymatic activity, adding another layer of posttranslational regulatory control to dynamic cellular processes.
For more than a decade, it has been speculated that the extent of lysine acetylation matches that of phosphorylation (Kouzarides, 2000). With this data set we provide evidence that this is indeed the case. Intriguingly, despite the observation that phosphorylation and acetylation both have broad cellular scopes, we have shown that they have distinct subcellular substrate patterns. On average the fraction of lysine-acetylated proteins that reside in the mitochondria is three times greater than that of phosphorylated proteins. Conversely, the fraction of phosphorylated proteins at the plasma membrane is twice as high as that of acetylated proteins. However, the subcellular distribution of lysine acetylation sites varies across tissues. Lysine acetylation is in general abundant in mitochondria, a large fraction of mitochondrial proteins carry the modification, and the average number of modified sites per protein is high, but the modification is particularly prevalent in mitochondria of energy-generating tissues. In brown fat more than 50% of the acetylation sites we identified reside on mitochondrial proteins. Among the sites are three modifications on the uncoupling protein 1 (ucp1), which is essential for the tissue's ability to dissipate energy as heat. Our data also reveal that the amino acids flanking the modified sites in brown fat mitochondria exhibit two significant sequence motifs: D-X-X-AcK and AcK-X-I.
Lysine acetylation has not previously been discussed in the context of secreted proteins, but we identify about 200 extracellular proteins that carry the modification. These proteins were primarily identified in adipose tissues, which likely reflect that adipose tissues are major endocrine organs (Kratchmarova et al., 2002; Saltiel, 2001). The functional roles of these lysine acetylation sites remain to be elucidated, as is also the case for the sites on the more than 400 plasma membrane proteins that we here show carry the modification. ER preparations purified from a human cell line were recently investigated in the context of lysine acetylation (Pehar et al., 2012). A total of 143 acetylated proteins were identified, which is about half the number reported herein. Two proteins highlighted in the study, GRP78 and CALR, were reported to harbor six and five acetylation sites, respectively. Although we have better coverage in our study, identifying 20 and 13 sites, respectively, a couple of sites reported by Pehar et al., 2012 were not covered in our data set. Artificial acetyl group transfers can be introduced in vitro by nonenzymatic reactions (Dormeyer et al., 2005) or by changes to a protein's C terminus (Pasheva et al., 2004). To prevent false positives, nonenzymatic acetylation should therefore be considered in the evaluation of in vitro studies of acetylated peptides. Pehar et al., 2012 investigated ERs purified from cells overexpressing an ER membrane acetyl-CoA transporter, which led to increased ER acetylation compared to endogenous levels. For GRP78 and CALR their acetylation profiles were further investigated by analyses of overexpressed C terminus-tagged proteins. The differences between the results of Pehar and colleagues and the results in this study could therefore either be a result of false positives introduced by the high levels of acetyl-CoA in their cell system, a change in the C terminus of the two proteins, or simply reflect that our compendium is not yet comprehensive.
The highest fractions of nuclear acetylation sites were identified in the lymphoid-containing organs, which are known to have high mitotic activity. The acetylation level of K19 and K24 on histone H3 correlates with transcriptional activity, and intriguingly, these particular sites are most abundant in the lymphoid tissues, such as thymus and spleen, that primarily consist of dividing cells with active cell-cycle machinery. There is further evidence in our data set for this observation by a significant overrepresentation of lysine acetylation-modified transcription factors in the same lymphoid tissues. For a few transcription factors, such as p53, RELA, and STAT3, it is already known that they are functionally regulated by lysine acetylation (Gu and Roeder, 1997; Hoberg et al., 2006; Wang et al., 2005). Our identification of a total of 388 acetylation sites on transcription factors indicates that lysine acetylation may be a more ubiquitous mechanism of transcription factor regulation than previously appreciated. The notion that the modified sites are more prevalent in mitotic compared to postmitotic tissues, such as brain and heart muscle, further favors a functional role of these sites. In the lymphoid tissues we identify significant nuclear sequence motifs for lysine acetylation sites. We show that although lysine acetylation sites on histones exhibit the motif K-X-X-X-AcK-X-X-X-K, sites on nuclear proteins in general and on transcription factors, in particular, exhibit preference for the motif G-AcK-P. A glycine at position −1 has previously been demonstrated to be part of a recognition motif for the nuclear CBP/p300 lysine acetyl transferase (KAT) complex (Bannister et al., 2000), and a high-resolution crystal structure of the KAT domain of the STAGA transcription coactivator-complex member GCN5 bound to either coenzyme A or a histone H3 peptide also revealed binding specificity for a random coil structure with this motif (Rojas et al., 1999), thus supporting the functional relevance of glycine preceding lysine as part of a nuclear recognition motif.
Our finding that lysine acetylation sequence motifs are compartment specific favors the debated existence of subcellular compartment-specific KATs (Sadoul et al., 2011). Although a mitochondrial KAT is further supported by our identification of acetylation sites on four proteins encoded by mitochondrial DNA, we cannot rule out the possibility that the sequence motifs are due to compartment-specific protein expression patterns. The observed sequence preferences could also in part be mediated by lysine deacetylates (HDACs). HDAC inhibitors are promising therapeutic agents for treatment of a variety of cancers (Marks et al., 2001). Nevertheless, the underlying molecular mechanisms and effects of the clinically administered HDAC inhibitors are largely unknown. It would not only be of high medical relevance to probe patient tumor samples for aberrant acetylation patterns, but delineating downstream in vivo targets of HDAC inhibitors is of equal importance. Therefore, we are confident that the methodology we have developed and applied to investigate lysine acetylation sites in tissue samples will open new avenues for large-scale investigations of lysine acetylation patterns in disease tissues and for phenotyping samples from patients with cancer.
Experimental Procedures
See Extended Experimental Procedures for detailed Experimental Procedures .
Rat Tissues and Peptide Extraction
Organs were quickly dissected from five Sprague-Dawley rats and snap frozen. Following heat inactivation tissues were homogenized and sonicated, proteins were acetone precipitated, resuspended in urea, and the concentration was determined. Proteins were reduced, alkylated, and digested with endoproteinase Lys-C followed by trypsin. Samples were desalted, and acetylated peptides were enriched using agarose-conjugated acetyl lysine antibody and separated by SCX fractionation before loading onto in-house packed C18 STAGE tips.
Eluted peptide mixtures were reconstituted in 2% MeCN, 0.5% AcOH, 0.1% TFA, and separated by online reversed-phase C18 nanoscale liquid chromatography on a 15 cm × 75 μm column packed with ReproSil-Pur C18-AQ 3 μm resin. A nanoflow EASY-nLC system (Proxeon Biosystems, Odense, Denmark) was connected through a nano-electrospray ion source to the mass spectrometer. Peptides were separated by a linear gradient of increasing acetonitrile in 0.5% acetic acid for 180 min with a flow rate of 250 nl/min. The MS/MS was performed on a LTQ Orbitrap Velos mass spectrometer (Thermo Electron, Bremen, Germany) using a top10 HCD fragmentation method. Full-scan MS spectra were acquired at a target value of 1e6 and a resolution of 30,000, and the HCD-MS/MS spectra were recorded at a target value of 5e4 and with a resolution of 7,500 using normalized collision energy of 40%. Raw MS files were processed using the MaxQuant software (ver.22.214.171.124 and v.18.104.22.168). Precursor MS signal intensities were determined, and HCD MS/MS spectra were deisotoped and filtered such that only the ten most-abundant fragments per 100 m/z range were retained. Acetylated proteins were identified using the Mascot search algorithm. HCD-MS/MS spectra were searched with fixed modification of Carbamidomethyl-Cysteine and variable modifications of oxidation (M), acetylation (protein N-term), Gln- > pyro-Glu, and acetylation (K). Initial precursor ion tolerance was 7 ppm, MS/MS tolerance 0.02 Da, and strict tryptic specificity with maximum two missed cleavages were required. Label-free quantification and validation were performed in MaxQuant. Acetylated peptides were filtered based on Mascot score, PTM (Andromeda) score, precursor mass accuracy, peptide length, and summed protein score to achieve an estimated FDR <0.01 based on forward and reversed identifications. Hierarchical clustering was performed in Perseus (Max-Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Munich) using Euclidian distance and average linkage clustering. Statistical evaluation of enriched Reactome pathways and GO terms for biological processes identified with the innateDB web tool (Lynn et al., 2008) were performed using a hypergeometric test and correcting for multiple testing by applying a Benjamini-Hochberg false discovery rate of 0.01. Sequence motif analysis was performed with iceLogo using percent difference as scoring system and applying a significance cutoff of 0.01.
Enzymatic Experiments
The coding sequences for human ALDOB and GPD1were cloned into pDEST-15, point mutations were introduced, and constructs were transformed into Rosetta cells. Recombinant proteins were extracted and incubated with glutathione Sepharose beads. The concentrations of purified proteins were determined, and the amino acid sequences were checked by MS. Enzymatic activities were determined as initial velocity measurements by monitoring NADH decrease as a function of time at 340 nm absorbance reads on a Biotek Synergy H4 reader.
Rat Tissues and Peptide Extraction
The study was carried out according to approved national regulations in Denmark and with animal experimental license granted by the Animal Experiments Inspectorate, Ministry of Justice, Denmark. Five Sprague Dawley rats (Crl:SD, male, 350 g, Charles River, Germany) were anesthetized with isoflurane and perfused (1.5 min, 30 ml/min) with isotonic saline containing protease inhibitors (0.120 mM EDTA, 14 μM aprotinin, 0.3 nM valine-pyrrolidide and, Roche Complete Protease Inhibitor tablets (Roche), pH = 7.4) before being decapitated. Organs were quickly dissected and snap frozen in 2-methylbutane. Dissected organs were: brain, pancreas, brown adipose tissue, testis fat, testis, liver, kidney, spleen, lung, stomach, intestine, thymus, heart, muscle and skin. Organs were heat inactivated (Denator T1 Heat Stabilizor, Denator, Gothenburg, Sweden) followed by tissue homogenization and micro-tip sonication on ice. Proteins were acetone precipitated and resuspended in urea solution (6 M urea/2 M thiourea, 10 mM HEPES, pH 8.0) and the concentration was measured (Quick Start Bradford Dye Reagent X1, Bio-Rad). 50 mg protein per tissue was reduced (final concentration 1 mM dithiothreitol, 750 rpm, 30 min), and alkylated (final concentration 5.5 mM chloroacetamide, 750 rpm, 20 min in darkness) before protein digestion with 250 μg endoproteinase Lys-C (Wako) (750 rpm, 3 hr). The samples were diluted with 25 mM ammonium bi-carbonate to lower the urea concentration below 2M, and then further digested with 250 μg modified trypsin (Sequencing grade, Promega) (750 rpm, 8 hr). Trypsin digestion was quenched by lowering pH ≈2 with trifluoroacetic acid (TFA). Samples were centrifuged (20 min, 16,000 x g) and supernatants were desalted and concentrated on Sep-Pack C18 Cartridges (Waters).
Enrichment of Acetylated Peptides
Peptides were eluted from the cartridges and acetylated peptides were enriched from the supernatants by incubation with agarose conjugated acetyl lysine antibody (acetyl lysine antibody, ICP0388, Immunechem) at 4C. Bound peptides were eluted from the agarose beads in 0.1% TFA. The peptides were subsequently separated by SCX fractionation on in-house packed micro-columns (Rappsilber et al., 2007; Weinert et al., 2011) and eluted at pH4, pH6 and pH8.5 (Wiśniewski et al., 2009). Organic solvents were evaporated using a vacuum centrifuge, and the peptides were acidified in 0.1% TFA, 0.5% acetic acid and loaded onto in-house packed C18 STAGE tips.
Peptide mixtures were eluted into a 96 well microtiter plates with 2x20ul 40% MeCN, 0.5% AcOH, followed by removal of organic solvents in a vacuum centrifuge and reconstitution of peptides in 2% MeCN, 0.5% AcOH, 0.1% TFA. The eluate was separated by online reversed-phase C18 nanoscale liquid chromatography on a 15 cm x 75 μm column in-house packed with ReproSil-Pur C18-AQ 3 μm resin (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany). A nanoflow Easy –nLC system (Proxeon Biosystems, Odense, Denmark) was connected through a nano-electrospray ion source to the mass spectrometer. Peptides were separated by a linear gradient of increasing acetonitrile in 0.5% acetic acid for 180 min with a flow rate of 250 nl/min. The tandem mass spectrometry was performed on a LTQ Orbitrap Velos mass spectrometer (Thermo Electron, Bremen, Germany) using a top10 HCD fragmentation method with the replicate experiments analyzed on a Q Exactive mass spectrometer (Thermo Electron, Bremen, Germany). Settings used on the LTQ Orbitrap Velos included full-scan MS spectra acquired at a target value of 1e6 and a resolution of 30,000, and the HCD-MS/MS spectra recorded at a target value of 5e4 and with a resolution of 7,500 using normalized collision energy of 40%. Settings used on the Q Exactive were identical to the 'fast' method as previously described (Kelstrup et al., 2012) with an isolation width of 1.3 m/z. Briefly, a target value of 1e6 for full-scan MS with a resolution of 70,000 at m/z 200 was set. Fragment scans were analyzed with a fixed ion injection time of 60ms measured at a resolution of 17,500 at m/z 200.
Identification and Quantification of Acetylated Peptides
Raw MS files were processed using the MaxQuant software (ver.22.214.171.124 and v.126.96.36.199), Max-Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Munich) by which the precursor MS signal intensities were determined and HCD MS/MS spectra were deisotoped and filtered such that only the ten most abundant fragments per 100-m/z range were retained. Acetylated proteins were identified using the Mascot search algorithm by searching all MS/MS spectra against a concatenated forward/reversed version of rat and mouse International Protein Index v.3.37 protein sequence database supplemented with protein sequences of common observed contaminants like human keratins and porcine trypsin. Human skeletal muscle samples were searched against a concatenated forward/reversed version of human International Protein Index v.3.68 protein sequence database. The HCD-MS/MS spectra were searched with fixed modification of Carbamidomethyl-Cysteine and we allowed for variable modifications of oxidation (M), acetylation (protein N-term), Gln- > pyro-Glu, and acetylation (K). Search parameters were set to an initial precursor ion tolerance of 7 ppm, MS/MS tolerance at 0.02 Da and requiring strict tryptic specificity with a maximum of two missed cleavages. Label-free peptide quantification and validation was performed in the MaxQuant software suite. Acetylated peptides were filtered based on Mascot score, PTM (Andromeda) score, precursor mass accuracy, peptide length, and summed protein score to achieve an estimated FDR < 0.01 based on the forward and reversed identifications. The minimum required peptide length was set to six amino acids. We required a minimum Mascot score of 10 and a minimum Andromeda score of 25 and a delta score to the next best match of at least 5.
Data Analysis
Data analysis was performed using Microsoft Office Excel and Perseus (Max-Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Munich) software. Hierarchical clustering was performed in Perseus using Euclidian distance and average linkage clustering.
Subcellular Compartment Pathway and GO Analysis
We grouped all lysine acetylated proteins based on their subcellular localization as defined by the GO term cellular component. For each tissue we calculated the fraction of identified acetylated proteins per compartment and calculated the deviations by dividing by medians for each compartment. Pathway and GO enrichment analyses were performed for proteins specific for tissue clusters against all other identified proteins residing in the same compartments using the innateDB web tool (Lynn et al., 2008). Enriched REACTOME pathways and GO-terms for biological processes were determined based on their corresponding P-values for over-representation in a given subcellular compartment. P-values were calculated using a hypergeometric test and corrected for multiple testing with a Benjamini-Hochberg. A cut-off of 0.01 was applied.
Sequence Motif Analysis
We performed sequence motif analysis using iceLogo with percentage difference as scoring system and a P-value cut-off of 0.01 using the Rattus Norvegicus protein sequence database as background. For heat maps: for all identified lysine acetylation sites as well as for lysine acetylation sites from each specific compartment we analyzed the amino acid sequences surrounding the sites by calculating their position-specific frequencies and dividing this by the amino acid frequencies of the Rattus Norvegicus protein sequence database. Significance for overrepresentation of identified motifs was evaluated by Fisher exact test calculations with a P-value cut-off of 0.05.
Expression of Recombinant Proteins
Gateway Entry clones of human ALDOB and GPD1 were obtained from the Invitrogen Ultimate ORF collection (Invitrogen). The coding sequences were cloned into pDEST-15 (Invitrogen). The lysine to glutamic acid (K120Q for GPD1 and K147Q for ALDOB) point mutations were introduced by PCR-based mutagenesis. All constructs were verified by sequencing and transformed into Rosetta cells (Novagen). Expression of recombinant proteins were induced with 1mM IPTG (Sigma Aldrich) overnight at 4°. Cells were harvested and washed with PBS. Proteins were extracted with Bugbuster (Novagen) supplemented with protease inhibitors, (Roche Complete Protease Inhibitor tablets, Roche), 50mM Tris-HCl (pH 7,5), 150 mM NaCl, 1mM DTT, 1 μl/ml Benzonase and 200 μg/ml Lysozyme. The extract was subjected to sonication and snap freezing in liquid nitrogen. After clarification by centrifugation the extracts were incubated on Glutathione Sepharose Beads (GE Healthcare) overnight at 4°. After washing the proteins were eluted with 15 mM reduced glutathione (Sigma Aldrich) supplemented with 50mM Tris-HCl (pH 7,5), 150 mM NaCl and 1mM DTT. The purified proteins were analyzed by SDS-PAGE and the concentration determined (Quick Start Bradford Dye Reagent X1, Bio-Rad). The amino acid sequences of the purified proteins were furthermore checked by mass spectrometry.
Enzyme Activity Assay
The catalytic activity of GPD1 toward dihydroxyacetone phosphate was investigated by measuring the simultaneous oxidation of NADH. The GPD1 activity was measured in a 200 μl reaction volume containing GPD1, 1 mM D-Fructose-1,6-bisphosphate, 150 μM NADH, 2 U Aldolase (Sigma), 2 U Triosephosphate isomerase (Sigma) in 50 mM Tris-HCl. The enzyme activity is determined as initial velocity measurements by monitoring the NADH decrease as a function of time at 340 nm absorbance reads on a Biotek Synergy H4 reader. Reconstituted purified wild-type or mutant GPD1 (0.8 μg/ml) was diluted in assay buffer and added to the other reaction components resulting in 0.83 μg/ml wt and 0.83-212 μg/ml mutant GPD1 in the assay. Similarly, the catalytic activity of ALDOB toward fructose-1,6-bisphosphate was assayed by the downstream oxidation of NADH. Reconstituted purified wild-type or mutant ALDOB (13 μg/ml) was mixed in a 50 mM Tris-HCl buffer with 1 mM D-Fructose-1,6-bisphosphate, 150 μM NADH, 2 U Triosephosphate isomerase and 150 μg/ml GPD1 (wt). The cleavage of fructose-1,6-bisphosphate was measured as initial velocities using 3.3 μg/ml wt and 3.3 μg/ml - 212 μg /ml mutant ALDOB. Both enzymatic assays were conducted in triplicates at room temperature, and the results are shown as mean ± SEM. Assay detection limits are established based on blank samples without enzyme and converted to units of μg/min/mg using the enzyme concentration 212 μg/ml.
CPR PTM Resource
The CPR PTM Resource is a web-based data repository that integrates high-confidence in-vivo post-translational modification sites that we have identified by mass spectrometry-based proteomics in different tissue samples from various species. It is based on a MySQL database and developed with the Perl/CGI language. Modified proteins can be visualized based on their Uniprot identifiers. For each modified site in a protein we list the matching acetylation motifs we have identified and use the Reflect service to add additional information about the modified proteins.
Protein-protein interaction networks
Protein-protein interaction networks were built using a previously described up to date interaction network of quality controlled human protein interactions (InWeb, Lage et al., 2007 (Lage et al., 2007)). In brief, InWeb combines reported protein interactions from MINT, BIND, IntAct, KEGG annotated protein-protein interactions (PPrel), KEGG Enzymes involved in neighboring steps (ECrel), Reactome and others. All human interactions are pooled and interactions in orthologous protein pairs passing a strict threshold for orthology are included. Each interaction is assigned a probabilistic score based on the neighborhood of the interaction, the scale of the experiment in which the interaction is reported and the number of different publications in which the interaction has been cited. To generate a network InWeb is scanned for interaction partners of each of the tissue-specific acetylation data sets (the input sets). For each input set, various parameter settings (density of interactions and different thresholds of confidence scores) are tested to identify the most significant network for the input set. The significance of each of the generated networks is determined by randomization testing. Specifically, for an input set of N input proteins yielding an interaction network (connected component) with G input proteins and T total proteins, a network score (NSinput) is determined. This network score is the fraction of input proteins of all proteins in the network (G/T). The significance of the network score is next determined by empirically estimating the probability of observing a similar or better network score in networks generated by using 10 000 random input sets of size Ninput. The random gene sets are chosen so the degree distribution of proteins in the random sets approximate the input set. As each query generates a varying number of networks (connected components) the probability estimates can be calculated from the total amount of networks produced by all 10 000 randomizations that have a network score > NSinput. All these algorithms have been thoroughly described elsewhere (Bergholdt et al., 2007; Lage et al., 2010). Furthermore, to probe for pathological processes associated with the tissue-specific protein-interaction networks, we analyzed each of the networks for genes known to be mutated in familial diseases, as described in Online Mendelian Inheritance in Man (OMIM®. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, MD), January 2011). The p values were adjusted for multiple hypothesis testing by Bonferroni correction.
We thank all members of the Department for Proteomics at the Center for Protein Research for scientific discussions and Dr. Nikolai Nordsborg for help with collecting human samples. The Center for Protein Research is partly supported by a generous donation from the Novo Nordisk Foundation. This work was supported by the Seventh Framework Programme of the European Union (Contract no. 262067- PRIME-XS) and the research career programme Sapere Aude from The Danish Council for Independent Research for Medical Sciences (to A.L. and J.V.O.). A.L. and J.V.O. designed all of the experiments, A.S. and C.L. coordinated animal and human sample handling, respectively, A.L. completed all sample preparation, A.L. performed MS analysis, B.T.W. provided input on SCX fractionation, C.D.K. provided input on Q Exactive measurements, K.L. generated protein interaction networks, D.B.B.-J. and T.S. performed enzyme experiments, A.D. made the MySQL database, A.L. and J.V.O. performed data analysis, B.T.W. and C.C. provided input on manuscript, and A.L. and J.V.O. wrote the paper.
Supplemental Information
- Table S1. All Modified Peptides Identified (XLS 22315 kb)
- Legends for the column headers are provided in sheet 2.
- Table S2. All Quantified Lysine Acetylation Sites (XLS 13246 kb)
- Legends for the column headers are provided in sheet 2. In sheet 3, we have extracted all lysine acetylation sites identified on histone proteins.
- Table S3. All Quantified Lysine-Acetylated Proteins (XLS 4073 kb)
- Legends for the column headers are provided in sheet 2.
- Table S4. Human Skeletal Muscle Lysine-Acetylated Peptides (XLS 2057 kb)
- Sheet 1, all acetylation sites; sheet 2, all modified acetylated peptides identified; sheet 3, a list of all acetylated proteins. Legends for the column headers are provided in sheet 2.
- Table S5. All Identified Transcription Factors with Lysine Acetylation Sites (XLS 32 kb)
- Transcription factors with lysine acetylation sites that are upregulated in the lymphoid containing tissues are highlighted in gray.
Web Resources
The URLs for data presented herein are as follows:
Mascot, http://www.matrixscience.com
Online Mendelian Inheritance in Man (OMIM), http://omim.org/
Reflect, http://reflect.cbs.dtu.dk/index.html
TRANCHE, http://www.proteomecommons.org
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Publication Information
Received: November 29, 2011
Revised: May 22, 2012
Accepted: July 18, 2012
Published online: August 16, 2012


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(1-1, 0-0) |
Date | September 15, 2011 |
(2-0, 0-0)) |
Passes Broken Up | 7 | 6 |
QB Hurries | 3 | 4 |
Fumbles Forced | 1 | 2 |
Interceptions | 2 | 2 |
Sacks | 3.0 | 4.0 |
Tackles for Loss | 10.0 | 8.0 |
3rd Down Conversion % | 31.03% | 62.96% |
Rushing Yards Allowed | 71.00 | 114.50 |
Rushing Avg. Yards/Attempt | 2.45 | 3.75 |
Passing Yards Allowed | 106.00 | 263.50 |
Passing Avg Yards/Attempt | 4.1 | 8.2 |
It's sorta amazing what a small sample size can do as it appears in a lot of the big play categories, New Mexico and Texas Tech are similar. You could probably say that New Mexico is actually better in those big play categories, but it's the last five statistics that are probably pretty telling from how these two teams have fared this season.
If you need a refresher as to how Texas Tech did on third downs last year, it was 47.09% and DC Art Kaufman has helped orchestrate it down to 31.03%. Again, we all know that it's just two games against lower-level competition, but that's going to be a key statistic to watch over the course of the year. Alternately, New Mexico is allowing opponents to complete 62.96% of all third downs and that's problematic for the Lobos. Even against Southern, New Mexico allowed 7 of 13 third downs to be converted and Texas was 10 of 14.
There are obviously some encouraging things going on defensively. Despite Texas Tech having an okay day offensively, Texas Tech is still doing quite well and as I mentioned on Saturday, Texas Tech only allowed 73 yards of total offense in the second half on Saturday. That's a good way to end a game where there maybe appeared to be some holes in the defense. It is still encouraging to see just 2.45 yards allowed per rushing attempt. I still worry about this defense against a competent running team, but this defense isn't about completely shutting out an opponent, but rather it is about being a bit better than they were last year. This defense has come a long ways, but there is still a long ways to go.
I think it is also fair to say that Texas Tech's first two opponents are not passing teams and neither is New Mexico. So the passing yards allowed isn't going to be too incredibly important at this point of the season. Still, you also can appreciate the fact that the Texas Tech defense is allowing just 4.1 yards per attempt. For New Mexico, the Lobos allowed David Ash to complete 21 of 30 passes for 285 yards and 9.5 yards per attempt. I have a feeling that QB Seth Doege could be significantly better. I'd also add that it didn't really even appear that Texas tried to much rush the ball, especially in the first half, against New Mexico. Texas only ran the ball 31 times for 146 yards, which is not what I expected.
The offenses are after the jump.
Red Zone TD % | 69.23% | 100.0% |
3rd Down Conversion % | 62.96% | 48.00% |
Passing Yards | 363.00 | 52.00 |
Yards/Passing Attempt | 7.8 | 5.6 |
Touchdowns | Turnovers | 12 | 3 | 9 | 2 |
Turnover Margin | -1.00 | +1.00 |
Yards/Play | 6.82 | 5.31 |
Sacks Allowed / Game | 1.0 | 1.0 |
Rushing Yards | 182.50 | 276.00 |
Rushing Yards Per Attempt | 5.29 | 5.64 |
Another interesting statistic, which is red zone touchdown percentage is that New Mexico has had 5 opportunities in the red zone and converted all 5. Meanwhile, Texas Tech has had 13 opportunities and converted on 9. Again, these are small sample sizes, but an additional 8 opportunities in the red zone is good for Texas Tech. Still, this puts Texas Tech in the 40th or so range nationally for converting on the red zone opportunities. This could be improved.
Also telling is the third down conversions for each team and that near 70% conversion rate is good for second in the nation. I know that we get angry at a single third down that goes awry with a double-reverse, but I like trying to mix things up a bit and overall, Texas Tech has been spectacular on third downs.
One of the reasons why I added both touchdowns | turnovers and turnover margin is because there are time that one statistic is not as telling as the other. I like to see how far ahead the offense is in terms of touchdowns versus turnovers and if that figure ever gets close, then things have gone horribly wrong. Meanwhile, you can see how Texas Tech hasn't created nor had a ton of turnovers. This doesn't necessarily mean much now, but I think it will mean a lot in Big 12 play.
Saturday's performance helped beef up some relatively pedestrian statistics from Texas Tech in the first game. No matter the opponent, the passing yards and rushing yards and rushing yards per attempt are pretty darned good. The lone stat that sticks out a bit is the yards per passing attempt. I do think that Doege is doing a better job of getting the ball down the field. Doege and the passing offense has had 14 plays of +15 this year for 7 per game, while last year the offense averaged 6.5. It's a bit better and not all long plays are going to be completed, but it helps to push the envelope.
I'd also say that from just watching with my own two eyes, that the offense is better and more vertical. Mainly because I think we've seen 1 wide receiver screen this year and that was an incompletion. It feels like it is getting better.
For New Mexico, when I said that they were not a passing team, this is the reason why. This is also the reason why Dustin Walton walked-on at Texas Tech. Bob Davie is a triple-threat running team. I really am interested to see how the Texas Tech defense is able to stop a team that is 100% committed to running the ball.
All helmet images via The Helmet Project and thanks to College Football Statistics for these stats.


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- Nylabone Durable (the original Nylabone) is long lasting and specifically designed for strong chewers.
- He loves it! Review by Gizmo
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Kaberle: The Value of Speculation
As promised it has been a summer of comprehensive retooling both on the grind lines and perhaps more pertinently on the blueline. With Brian Burke hitting the fast forward on the once anticipated rebuild, the Leafs have become a tougher proposition with a prospects chart expected to feed into that ethos for years to come. Meanwhile, the defensive corps has become deeper and more pugnacious than any Leafs setup in the past decade… at least from a utilitarian standpoint.


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The Crimson Pirate (DVD)
MAN OF NINE LIVES AND 1000 SURPRISES! In the late 18th Century, Captain Vallo, his trusty mute partner Ojo and his crew of nefarious pirates scour the Caribbean searching for ships to plunder. This light-hearted action romp has everything you would expect from a pirate film: scurvy men, and a pretty damsel in distress!
Crimson Pirate, The (DVD)
DeVoteD DVD © 2014
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Item # 201238
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Plot Summary
Father and son journeying together toward the sea across a post-apocalyptic landscape, some years after a great, unexplained cataclysm has destroyed civilization and almost all life on Earth.
Movie Reviews from Rotten Tomatoes
75%- Reviews Counted: 201
- Fresh: 150
- Rotten: 51
- Average Rating: 6.9/10
Top Critics' Reviews
Fresh: Hillcoat does his best, and for the most part, he succeeds. The horrifically desolate landscape and the drab greys and cobalt blues of the scarred sky pervade every shot.
Fresh: A horribly credible, chillingly beautiful and wholly uncompromising drama. It's the end of the world, all right, but no one feels in the least bit fine.
Rotten: This one-note exercise in neo-medieval moodiness eventually dissolves into that perennial and most corny of Hollywood tropes: the search for redemption. A disappointment.
Fresh: The film is so beautiful. In this sort of stark, austere grim way it's incredibly beautiful.
Customer Reviews
Must be able to step outside into the Sun after watching movie.
One must be able to step outside into the Sun after watching this movie. That's how desperate, dreary, depressing, deathly, and whatever other words the thesaurus will come up with to describe the hopeless feeling this movies leaves the viewer with.
I will start out with the problems:
1. Get rid of the music. It has no place in this world. The story goes so far as to explain music has no place in this world and yet the simple mistake of putting music in there was made. No Country For Old Men had no music, why couldn't this one? Also, the music included is entirely inappropriate because it ends up feeling sentimental instead of like some kind of disease is strangling the life out of you as slowly as possible.
2. Word of mothers who will have children in this world, only to eat them, barely sneaks into this movie. It should have been a very important scene in the movie because of how well it shows the difference between our world and the one McCarthy Wrote. Babies are not made for survival of the species; there is no hope for survival of the species, only ones own survival, and so cannibalism in some extreme form is practiced.
The good:
1. Amazing atmosphere. Not for children. This can easily TRAUMATIZE children. I know I am scarred for life by McCarthy's story.
2. For myself a son of a father who has always been there, I can instantly relate to the main characters in this movie. I have read in an interview, Cormac McCarthy received many letters from Fathers who found it an extremely profound experience and were deeply connected to the main characters.
3. Fantastic visuals of this dying world. No explanation is needed for why the world is dying, it just is, which goes back to 1.
4. The sense of paranoia and fear is extremely well placed at times.
5. Some key scenes were implemented very well. Such as the 'cellar', the 'old traveller', and the 'thief'.
6. Viggo gives it everything. He looks and acts emaciated, starving for a chance to eat food for both the body and the mind. He wants to forget the old world, yet famished for new fond memories, he cannot forget.
I highly recommend this movie with one caveat, be able to step outside into the sun after you're done watching it, because you're going to need it.
So Oscar worthy
A beautiful story of survival and the love between a father and son in an otherwise loveless hell-on-earth. I was deeply moved by this film and was shocked when it was ignored by the Oscars. I assume it was because of the brutally bleak nature of the film, which at times is hard to watch, but really no more disturbing than humanity in it's current state.
Will stay with you days after you've watched it.
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