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Different Frequencies of Drug Resistance Mutations among HIV-1 Subtypes Circulating in China: A Comprehensive Study

The rapid spreading of HIV drug resistance is threatening the overall success of free HAART in China. Much work has been done on drug-resistant mutations, however, most of which were based on subtype B. Due to different genetic background, subtypes difference would have an effect on the development of drug-resistant mutations, which has already been proved by more and more studies. In China, the main epidemic subtypes are CRF07_BC, CRF08_BC, Thai B and CRF01_AE. The depiction of drug resistance mutations in those subtypes will be helpful for the selection of regimens for Chinese. In this study, the distributions difference of amino acids at sites related to HIV drug resistance were compared among subtype B, CRF01_AE, CRF07_BC and CRF08_BC strains prevalent in China. The amino acid composition of sequences belonging to different subtypes, which were obtained from untreated and treated individuals separately, were also compared. The amino acids proportions of 19 sites in RT among subtype B, CRF01_AE and CRF08_BC have significant difference in drug resistance groups (chi-square test, p<0.05). Genetic barriers analysis revealed that sites 69, 138, 181, 215 and 238 were significantly different among subtypes (Kruskal Wallis test, p<0.05). All subtypes shared three highest prevalent drug resistance sites 103, 181 and 184 in common. Many drug resistant sites in protease show surprising high proportions in almost all subtypes in drug-naïve patients. This is the first comprehensive study in China on different development of drug resistance among different subtypes. The detailed data will lay a foundation for HIV treatment regimens design and improve HIV therapy in China.

Introduction 30 years has passed since human immunodeficiency virus (HIV) was confirmed as the pathogen of acquired immunodeficiency syndromes (AIDS) [1].This pandemic have already spread all over the world, infected millions of people and caused enormous social and economic loss. Highly active antiretroviral therapy (HAART) offensively suppressed HIV replication in vivo, prolonged life of HIV infected persons and promote their live quality, however, the occurrence of drug resistance impair this effect greatly and has become the main cause of antiretroviral therapy (ART) failure [2].
High diversity was the main characterization of HIV. Two types of HIV, HIV-1 and HIV-2, were identified based on the genetic difference. The former is the main type that has caused global pandemic and representing absolutely most of the HIV isolates, while the latter is restricted in western and central Africa and very few cases out the continent only account for no more than 2% of all HIV infection [3]. HIV-1 contains four groups (M, N, O and P) [4][5][6], group M is the major group responsible for the AIDS pandemic which including nine pure subtypes (A to D, F to H, J and K) as well as more than 50 circulating recombinant forms (CRFs) and many unique recombinant forms (URFs) [7]. So far, all antiretroviral drugs were designed based on subtype B for it is the major subtype prevalent in the US and Western Europe, but this subtype caused only approx. 10% of all HIV infection [8]. High level of genetic polymorphisms was found among HIV sequences belonging to different subtypes, which may cause the frequencies of drug resistance mutations different among different subtypes. Illustration of the difference will be helpful to analyze why and how drug resistance mutations appear and meaningful for clinic individualized antiretroviral therapy.
Among the 9 antiretroviral drugs freely provided by the Chinese government presently, zidovudine(AZT), lamivudine(3TC), stavudine(d4T), didanosine(ddI) and tenofovir(TDF) belong to nucleoside reverse transcriptase inhibitors (NRTIs); efavirenz(EFV) and nevirapine(NVP) belong to non-nucleoside reverse transcriptase inhibitors (NNRTIs); indinavir/r(IDV/r) and lopinavir/r(LPV/r) belong to protease inhibitors (PIs) [9]. The first line ART regimens were usually composed of two NRTIs (usually contain two of d4T, AZT or 3TC) and one NNRTIs of NVP or EFV. The other drugs always act as substitutes used for those who failed ART or some special populations as pregnant women and those who co-infected with other diseases as tuberculosis, HBV and so on [9,10]. Generally, viral subtypes at a population level were always not considered during ART regimens selection, despite the genetic difference among HIV-1 subtypes may confer differently to the development of drug-resistance.
In this study, HIV-1 strains belonging to main subtypes prevalent in China, including subtype B, CRF01_AE, CRF07_BC and CRF08_BC, were collected to investigate the difference of drug resistant mutations among different subtypes. Furthermore, the correlations between specific drug-resistant mutations and subtypes were explored, which may be helpful in alerting and adjusting therapeutic schedule to promote the effect of antiretroviral treatment.

HIV-1 sequences
The pol region, especially the region coding protease and the start 720 base pairs of reverse transcriptase (RT), is always used for HIV genotype drug-resistance test. Three kinds HIV-1 sequences of that region were included in this study: i) interested sequences fragments downloaded from the Los Alamos HIV sequences database (http://hiv-web.lanl.gov). All problematic sequences were excluded and only one sequence was selected per patient; ii) sequences generated in our laboratory for annual drug resistance surveillances and epidemiological analysis in the past 3 years were also included. All sequences were produced by nest RT-PCR with plasma viral RNA as template, then determined with pyrosequencing method; iii) sequences provided by the AIDS Care Center of the Yunnan Infectious Disease Hospital during drug resistance surveillance in 2012. To ensure data quality, sequences that contain stop codons and individual resistance codons with more than 2 ambiguities base per nucleotide position or with 2 ambiguities bases, which may be the result of contamination in RT-PCR or bad sequencing, were excluded from the analysis.

Sequences subtyping and drug resistance evaluation
Subtypes of the sequences from the HIV sequence database were already determined in the database and downloaded directly. Sequences generated in our laboratory and those provided by the AIDS Care Center of the Yunnan Infectious Disease Hospital were subtyped online with REGA HIV-1 subtyping tool 3.0(http://www.bioafrica.net), which incorporates both phylogenetic and boot scanning methods in an automated process to identify subtypes, CRFs and URFs of query sequences [11,12]. MEGA 5.1 was used to perform phylogenetic analysis to identify the subtypes of sequences which could not be determined with REGA. All sequences of subtype B, CRF01_AE, CRF07_BC and CRF08_BC were included into drug resistance evaluation, which were performed online at HIV drug resistance database (http:// www.hivdb.stanford.edu).
Sequences were sorted into several groups based on subtypes and drug resistance, i) resistant sequences group was make up of all four subtypes sequences with any major and/or minor drug resistant mutation(s); ii) susceptible sequences groups were composed of sequences containing no drug resistant mutations, and sequences were further subdivided into three small groups according to ART conditions: a) no background information group, which contains the sensitive sequences download from the HIV sequence database with little background information and no clear data about ART, those sequences were excluded from further analysis; b) drug naïve susceptible group, which contains sensitive sequences isolated from patients never expose to ART drugs; c) ART susceptible group, which contains sensitive sequences isolated from patients who received ART.

Drug resistant mutations
Drug resistant mutations were defined as any differences from the consensus B amino acid sequence [8] and selected mainly based on HIV drug resistance database and published data including all listed major mutations, minor mutations and other mutations which are polymorphism sites or occurs in combination with mutations obviously influence drug resistance level. A polymorphism is defined as a mutation that occurs in at least 1% of a population not exposed to selective drug pressure [13,14]. Drug resistance mutation sites are selected based on drugs used in China as follows: NRTIs resistance related sites 40

Statistical analysis
Sequences were aligned with BioEdit v7.0 and manually edited before translating into amino acids. The frequencies of amino acids at every drug resistance site were calculated. To analyze the differently distribution of amino acids among different subtypes, chi-square or fisher's exact test were fulfilled with SPSS v17.0 software. If positive results were observed, Kruskal Wallis test was performed to ascertain whether the difference was due to genetic barriers of codons.

HIV-1 sequences overview
A total of 3624 sequences were downloaded from HIV sequences database, 1483 sequences were generated in our laboratory and 335 sequences were provided by the AIDS Care Center of the Yunnan Infectious Disease Hospital, and there were 1984 subtype B, 1696 CRF01_AE, 502 CRF07_BC and 924 CRF08_BC sequences respectively included in this study after exclude those cannot meet the demand. For analytic convenience, nucleotide(s) insertion and deletion comparing to subtype B consensus sequence were omitted, the whole sequence was separated into protease region (amino acid: 1-99) and RT region (amino acid: 1-240) ( Table 1).

Different distribution of drug-resistant mutations is observed among subtype B, CRF01_AE and CRF08_BC
To analyze the distribution of drug-resistant mutations among different subtypes, 38 sites locating in RT region were analyzed (PIs-resistant mutations were not analyzed because only 73 PIsresistant sequences were obtained totally, especially CRF07_BC and CRF08_BC with only 4 and 7 sequences respectively). All drug-resistant mutations identified based on subtype B were found in at least one of the other two subtypes. Significantly different distributions were observed in 19 sites among subtype B, CRF01_AE and CRF08_BC (CRF07_BC was not considered due to a small sample size, chi-square or fisher's exact test, p,0.05). Among of them, three sites, including 103, 181 and 184, were found mostly prevalent (more than 20%) in all of three subtypes. The distributions of other drug resistance mutations were differently among subtypes, sites 41, 69, 101, 106, 179, 190, 210 and 215 were dominant in subtype B, while sites 68, 69, 75, 101, 106, 179, 190, 210, 215 and 238 in CRF01_AE and sites 41, 69, 101, 179 and 190 in CRF08_BC, which showed higher prevalent ratios than 10% respectively ( Figure 1). Further analysis on codons of those sites show that synonymous mutation of amino acids caused by single base mutation were exist in all sites except sites 41,184 and 230, while nonsynonymous mutation of amino acids from 1 to 4 in different sites caused by different number of bases mutation were existed in almost all sites. Some usually occurred mutations like M41I, K65N, V75AS, K101P, E138K, Q151L, V179F and G190EQ were not observed in this study. Genetic barriers, which were defined as the number of bases change for a virus to develop resistance and escape select pressure from special drugs [16], were believed to play certain roles in the development of HIV drug resistance. In this study, 5 sites (69, 138, 181, 215 and 238) among the 19 sites being analyzed were shown to contain significant differences among subtypes (Kruskal Wallis test, p,0.05) ( Table 2). This observation may explain why drug resistance develops at a similar rate during the antiretroviral therapy in China irrespective of subtype prevalence. In addition, only few of minor drug resistance mutation sites as 179 in subtype B, 75, 179, 238 in CRF01_AE and 179 in CRF08_BC account for preponderant proportion in corresponding subtypes compared that almost all major drug resistance mutation sites play dominant roles in all subtypes.
Polymorphism in sites related to drug-resistance was found differently among subtypes in drug-naïve individuals To compare the polymorphism of genetic background in sites related to drug resistance, sequences obtained from drug-sensitive strains which were isolated from drug-naïve individuals were analyzed. To guarantee that all sequences were obtained from drug-naïve individuals, only sequences generated in our laboratory with a clear clinical background were used. The analysis will be useful to explore the background of drug resistance sites and distinguish polymorphisms from drug resistant mutations. For subtype B, all sites matched the consensus sequence in RT region well except sites 69, 138, 179 and 230, which were present in 1-4% of sequences analyzed. However, amino acids proportion of the other three subtypes were more complicated especially in CRF01_AE and CRF08_BC ( Figure 2). Sites 68, 69, 75, 106, 118, 179, 210, 238 in CRF01_AE, sites 41, 101, 179 in CRF07_BC and sites 68, 69, 101, 106, 138,179 in CRF08_BC with obvious higher mutated proportions (2-74%), which should classified as a polymorphism site in respective subtypes. The result of drug resistance mutation sites in protease region was complicated and difficult to understand because so many sites with dominant proportions in drug naïve sensitive sequences. Several sites including 35, 36, 63, 71, 77, 89 and 93 show surprising high mutated amino acid proportions 5-98% in almost all subtypes despite according to the HIVdb Genotypic Resistance Interpretation Algorithm those mutations did not confer to drug resistance due to a small mutation scoring change. For example, site 71 in subtype B accounts for about 40% of mutated amino acids, this proportion apparent higher than that reported in previous published articles for A71T/V only occurred in 2-3% untreated persons and A71I/L were nonpolymorphic mutations that occurred with multiple PIs-related drug resistance mutations. Similar conditions were observed in most other sites suggesting that those mutations occurred and/or were selected during the process of virus replication in vivo without exposure to ART. Therefore accurate analysis of amino acids in drug resistance mutation sites among untreated population is not only necessary but helpful to better understand the drug resistance background status of HIV-1 PIs in China and this will provide some useful information for the application of PIs in future to get satisfactory therapic effect.
Different frequencies of drug-resistance related sites were observed in susceptible strains isolated from treated individuals Considering polymorphism at sites associated with HIV drug resistance may show different results under drug pressure, the distributions of amino acids at sites related to drug resistance among different HIV strains susceptible to antiretroviral drugs isolated from ART treated individuals were investigated. All sequences were collected during drug resistance annual surveillance and epidemiological study in our laboratory with clear background. More sites with higher proportion of mutated amino acids were observed in RT region in treated population as sites 103, 106, 118 in subtype B, sites 41, 184, 230, 238 in CRF01_AE, sites 69, 103, 210 in CRF07_BC. However, sites associated with drug resistance as 68, 106, and 179 in CRF08_BC show lower proportion of mutated amino acids under drug pressure (Figure 3). Those results suggesting that antiretroviral drugs play certain roles in induce and/or select mutations. Interestingly, the proportions of mutated amino acids in several sites related to drug resistance were lower in protease of respective groups despite little even no exposure to PIs and this further proved that drugs may have effects on HIV genetic mutations even in an indirect way. What we emphasize here is drug resistance mutation sites always compatible with polymorphism sites for the latter usually contains at least two kinds of nucleotides even if encode synonymous amino acid often lead to the spatial structure change greatly and influence the affinity of antiretroviral drugs and their targets cause drug resistance finally.  Difference at drug-resistance related sites in drugsensitive strains between treated and untreated patients Use of drugs always influence the alleles of polymorphism sites in targeting region, which may have effect on the development of drug-resistance. In this study, the amino acid proportions of mutated sites associated with drug resistance of each subtype between the drug naïve and ART treated sensitive sequences were also compared. More mutation sites with higher mutated amino acid proportions were observed in almost all subtypes of the latter group, which reveals that antiretroviral drugs usually induce and/ or select several mutations hardly occurred in RT region of drug naïve sequences. Those mutations can be divided into three types based on their functions as follows: i) mutations not associated with drug resistance according to available public published articles so far like K101R, K103R, V106I and V179I; ii) mutations that alone decrease susceptibility and contribute to drug resistance very limited usually work in combination with certain drug resistance mutations like V75I, V179F and L210W; iii) mutations not reported previously for low proportion whose conference to drug resistance are uncertain. What's more impress is that those sites in subtype B also emerged in at least one of other three subtypes as that in drug resistance sequences. In contrast, despite few sites show apparent difference between the drug naïve and treated sensitive groups, most sites in protease region were similar possibly due to the absent use of PIs in China.

Discussion
In this study, we fulfilled, to our knowledge, the first comprehensive study on amino acid distributions of drug-resistant sites among HIV subtypes prevalent in China, though studies in this areas have been carried up for more than 10 years [17][18][19][20][21][22][23]. As the dominant subtype prevalent in modern countries, subtype B was studied in more details than other subtypes. Most genetic characterizations of drug-resistant strains were also deduced basing on subtype B strains. However, the most studied subtype B caused only 12% of global infections, while subtype C was responsible for nearly 50% of prevalent infections and 47% of all new infections in the whole world [23]. More and more studies showed that HIV-1 subtype diversity had great effects on the development of HIV drug resistance, data on baseline antiretroviral susceptibility derived from studies of subtype B may not be applicable to non-B subtypes. Several drug resistance mutations were only identified in specific subtypes or showed different prevalence among different subtypes [3]. Furthermore, some strains were showed naturally resistant to antiretroviral drugs, for example, HIV-2 is intrinsically resistant to almost all NNRTIs. So it is urgent to illustrate the influence of HIV-1 subtypes on antiretroviral treatment and drug resistance development, which will be helpful to guide clinic antiretroviral therapy in design treatment strategies basing on subtype identification.
The subtype B virus is prevalent in China and the sequences included in this study were mainly Thai B, which was genetically distinct from the subtype B that dominant in the US and Europe as European B. Differences between Thai B and European B are mainly based on the C2-V3 region of the env gene, especially the motif sequences at crown of the V3 loop. In European B variants, the typical sequence is GIHIGPGRAFYTTG, while in Thai B the dominant pattern is SIPLGPGQAWYTTQ [24][25][26]. Considering that ART drugs targets were encoded by pol gene, which is more conservative and stable during viral replication in vivo for structure and function maintenance, so it's acceptable that the drug resistance of Thai B variants can be evaluated by the Stanford HIV drug resistance database which are based on data mainly from European B. Furthermore, despite CRF07_BC is a prevalent virus in China, few drug resistant sequences were collected. CRF07_BC is mainly epidemic in IDUs and MSM, for which population HAART and HIV drug resistance surveillance were hard to be fulfilled. With the scaling up of free therapy in China, more patients infected with CRF07_BC will be included into therapy and this may explain why most CRF07_BC variants included were drug-susceptible. In the future, our group will cooperate with first line workers to reinforce the drug resistance surveillance of CRF07_BC.
Mutation from a wildtype to a drug resistant codon could be influenced by the number and type of nucleotide(s) [16]. For example, it was proved that transitions (the replacement of a purine by another purine or a pyrimidine by another pyrimidine) are for steric reasons occurring on average 2.5 times more frequently than transversions (the replacement of a purine by a pyrimidine and vice versa) [27]. Furthermore, the number of hydrogen bonds between paired nucleotides may also affect the ratio of mutation. Since only two hydrogen bonds were identified between AT basepair while three hydrogen bonds were between GC basepair, it is reasonable to find more mutations at AT polymorphism sites. High level of polymorphism at drug-resistance related sites among different subtypes definitely affects mutation sites or patters. In this study, obvious disparities among HIV-1 subtypes were observed at drug-resistance related sites with Figure 3. Subtype-specific drug resistance mutation sites analysis based on ART sensitive sequences. Note: left part based on RT region and right part based on protease region, horizontal numbers indicate drug resistance mutation sites with significant difference among subtypes(chisquare or fisher's exact test, p,0.05), vertical percentage indicate the proportion of mutated amino acids differ from the subtype B consensus sequence. doi:10.1371/journal.pone.0091803.g003 different genetic background. Therefore, polymorphisms at drug resistance related sites may contributed differently to the occurrence of HIV drug resistance and should be given more concerns during the surveillance and design of antiretroviral therapeutic schedules.
The amino acid distributions of drug-resistant mutations sites showed significant difference among HIV-1 subtypes prevalent in China. However, all those sites that determined basing on subtype B strains could be found in at least one non-B virus, which was in accordance with previously published research. The most prevalent drug-resistant mutation sites were K103, Y181 and M184 in all subtypes, suggesting that the HAART regimens may play important roles in selecting the drug-resistant mutations irrespective of HIV subtypes. K103 and Y181 associated drug resistance mutations conferred high level resistance to NVP and EFV, while M184 associated drug resistance mutation cause high level resistance to 3TC and low level resistance to ddI and abacavir (ABC). Other high frequency (more than 10%) drug resistance mutation sites as M41, T69, K101, V106, V179, G190, L210 and T215 were also shared among subtype B, CRF01_AE and CRF08_BC. Among of them, M41, T69, L210 and T215 make up the thymidine analogue-associated mutations (TAMs) and confer high level resistance or low susceptibility to AZT, d4T, ddI, ABC and 3TC; K101, V106 and G190 were NNRTI-associated mutations contribute resistance to NVP, EFV and ETR. Most of those drugs were included in first and/or second line regimens used in China. Come to the conclusion that mutations listed above were all selected under drug pressure except V106 in subtype B, V179 and K238 in CRF01_AE and T69 and V179 in CRF08_BC due to little difference of prevalence between susceptible and resistance groups and should be owing to polymorphism sites in corresponding subtypes. Different to RT region, high level of polymorphism at drug-resistance related sites were found in protease region. It probably correlates to long time selection and viral evolution in vivo, so host races, geography distribution may have influence. Some sites (for example, M46L in CRF01_AE) were demonstrated in high level in drug-naïve population and should be distinguished for further study and considered in clinic therapy.
Several factors may affect the development of HIV-1 drug resistance in vivo: First, High speed of HIV replication and errorprone reproduction of reverse transcriptase. In untreated patients, the total number of productively infected cells in lymphoid tissue estimated to be approximately 10 7 to 10 8 and can produce no less than 10 10 viruses per day [28,29]. Lack of proofreading activity of reverse transcriptase leads to high rate of mismatch introducing on average one mutation for each viral genome transcribed [23,30,31]. Second, genetic barriers conferred by genetic background. Virus single mutation could quickly arise drug resistance to NVP, 3TC or emtricitabine(FTC), but other NRTIs need more mutations which conferred higher genetic barriers to generate drug resistance [32]. Third, single nucleotide polymorphism sites (SNPs) in host genome. It was proved that host genetic polymorphism in some genes could influence the absorption, distribution, metabolism and excretion of certain drugs, and further affect drug concentration in blood, which will lead to changing of effective pressure and production of drug resistance [33,34]. For example, SNPs in cytochrome P450 and the ATPbinding cassette family genes can greatly affect the blood concentration of ART drugs and further put impact on treatment effectiveness [35][36][37][38][39][40][41][42]. Other behavioral factors, such as good adherence, were also necessary to ensure success ART treatment, which had been absolutely confirmed [43].
In conclusion, we analyzed the distribution of amino acids at drug-resistant sites among HIV-1 subtypes prevalent in China, including subtype B, CRF01_AE, CRF07_BC and CRF08_BC. Although almost all mutations in subtype B were found at least in one non-B virus, different distributions of drug resistance mutation sites among HIV-1 subtypes were identified. The results hint that HIV-1 drug employment should be individualized, drugs with high genetic barriers should be given more consideration. The detailed data demonstrated in this study will be helpful for design regimens compatible for Chinese according to the prevalent subtypes.

Supporting Information
File S1 (DOC)


Human Surfactant Proteins (SP-) A1 and SP-A2: to Include or Not in Surfactant Replacement Therapy, and If Yes, Both or Which One?

Based on a large number of animal studies, surfactant protein A plays important roles in lung innate immunity under basal conditions and in response to various insults such as infection and oxidative stress. SP-A interacts with the Alveolar Macrophage (AM), the sentinel cell of innate immunity, and regulates many of its functions. These include the ability of the AM to produce cytokines and to carry out phagocytosis of various pathogens. Moreover, the AM proteomic expression profile has been shown to be significantly affected by SP-A. In a study where SP-A -/mice were treated (or rescued) in vivo with a single dose of human SP-A, the treatment nearly restored the AM proteomic expression to that of the wild type [1], supporting a role of SP-A on AM protein expression. Among the protein groups affected were actin-related/cytoskeletal proteins, which was the major group, proteins regulating inflammatory processes, and proteins related to Nrf2-mediated oxidative stress. Of interest, earlier studies have also indicated a role for SP-A in actin filament dynamics via its ability to enhance cell migration and AM chemotaxis [2], phagocytosis [3], other actin-dependent processes [4-6] and F-actin assembly [7]. The actin cytoskeleton is highly regulated and dynamic, with globular (G) and filamentous (F) actin, under the influence of many actin binding proteins, constantly changing by polymerization, depolymerization, branching, and remodeling, modulating inflammatory response and oxidative stress (Figure 1).

As shown in
signaling via NF-kB [8] and Nrf2 [9] can both depend on cytoskeletal changes, indicating that SP-A-mediated modulation of the actin cytoskeleton could have significant effects on AM responses. Moreover, the SP-A -/-rescue experiment [1] points to the possibility and feasibility of using SP-A as a therapeutic intervention in lung diseases influenced by innate immunity. Furthermore, based on animal studies [10] where small amounts of SP-A elicited significant differences in the AM proteome, it is possible that the SP-A amount needed may not be high, although, further experimentation will be needed to determine optimal amount and efficacy in the clinical setting.
However, humans, (unlike rodents) have two genes, SFTPA1 (SP-A1) and SFTPA2 (SP-A2) with several genetic variants identified for each SP-A1 and SP-A2 gene. These variants have been associated with many lung diseases including neonatal diseases, such as Respiratory Distress Syndrome (RDS) and Bronchopulmonary Dysplasia (BPD) [11]. The SP-A1 and SP-A2 gene products have been shown to differ in several functions related to innate immunity [12] and in surfactantrelated functions [13,14]. These differences have been reviewed previously [12] and include differences in their oligomerization status [13,15,16], their ability to form phospholipid monolayers [17], their ability to bind sugars [18], and their ability to enhance the phagocytic activity and cytokine production by the alveolar macrophages and macrophage-like cell lines, respectively [3,[19][20][21][22], as well inhibit surfactant secretion by Type II cells [13]. In most of these cases SP-A2 appeared to exhibit higher functional activity. However, in preliminary studies [23], we observed that SP-A1 produced a higher reduction in surface tension than SP-A2, with no significant differences observed between SP-A1 and SP-A that contained both SP-A1 and SP-A2. Furthermore, in the presence of oxidative stress the activity of SP-A2 to enhance phagocytosis may be reduced more than that of SP-A1 [3], and the SP-A2 resistance to trypsin is lower than that observed in SP-A1 and SP-A1/SP-A2 [15]. Collectively, these observations indicate that SP-A1 and SP-A2 may each be better for different functions in the lung i.e. either for surfactant-related functions and/or innate immunity. Thus, the addition of SP-A1 and/or SP-A2 in surfactant replacement therapies may be advantageous to both groups of functions, to innate immunity and surfactant, and in some cases and under certain conditions one may be better than the other. SP-A humanized Transgenic (hTG) mice, generated on the SP-A -/background where each hTG mouse carries a different human SP-A variant provide models to study the in vivo functional activity of each variant. With these mice we observed differences in the oligomerization pattern of SP-A1 and SP-A2 confirming in vitro findings and also observed that both SP-A1 and SP-A2 may be needed for an extracellular form of surfactant [14]. In addition, we have shown differences in the proteomic profile of AM derived from SP-A1 and SP-A2 hTG mice [24]. In other words, AM constitutively exposed to different human SP-A variants in vivo exhibit different expression profiles, and presumably this reflects different stages of functional activity either in one or more AM functions. In fact, the protein differences observed span several functional protein groups. Among these there were actin-related and cytoskeletal proteins, which was the major group of differentially regulated proteins by SP-A1 and SP-A2, as well as proteins involved in the regulation of inflammation, and proteins related to the Nrf2-mediated oxidative stress response [24]. As shown in Figure, remodeling of the actin cytoskeleton is central to several AM functions. Therefore, SP-A1 and SP-A2 are likely to differentially regulate several AM functions.
In the prematurely born infant, apart from potential exposure of the lung to varied levels of oxidative stress, one of the major complications is infection. Although innate immunity and the surfactant proteins could play a significant role in this process, none of the surfactant replacement therapies include the surfactant proteins SP-A1 and/or SP-A2, or SP-D [25]. Of interest, surfactant treatment of babies with RDS defined as "simple" or with pneumonia indicated that in the latter group, surfactant treatment was less effective [26]. In addition, after surfactant therapy, neonates with respiratory failure and Group B streptococcal infection, although most of them showed an improvement in gas-exchange, this improvement was slower compared to RDS [27]. Whether the outcome in RDS with or without infection, or in other diseases beyond RDS [28] would or could be better if SP-A is included in the surfactant preparations or given alone remains to be determined. Of interest, the efficacy of surfactant in its current form on bacterial pneumonia in preterm infants, remains an open question. An attempt to assess randomized clinical trials for efficacy of surfactant in late term and preterm infants with bacteria pneumonia could not reach any conclusions one way or another at the present time [29]. However, based on the available literature, and the role of human SP-A1 and SP-A2 on AM functions, it is imperative that considerations for including the surfactant proteins in existing surfactant preparations or using them individually in the absence of surfactant be investigated. Moreover, as noted above, SP-A1 and SP-A2 may also contribute to surfactant-related functions and therefore its potential therapeutic use may benefit these functions as well. Furthermore, considerations as to whether both or which genetic variant(s) for a given condition be used must not be overlooked. These questions must be investigated with further experimentation.  [1] show that SP-A has significant impact on the AM expression profile and specifically on the cytoskeletal/actin-related proteins. Based on the literature cytoskeletal changes may affect several signaling processes including NF-kB [8] and Nrf2 [9]. These processes in turn via transcriptional regulation modulate the inflammatory response and the response to oxidative stress. In addition cytoskeletal changes are key in AM activities such as phagocytosis, motility, and cell shape. Thus, SP-A, via its ability to alter expression of cytoskeletal/actin-related proteins in the AM, may affect several of the AM functions or responses [i.e. inflammation, oxidative stress, phagocytosis, and other]. For example, human SP-A variants have been shown to differentially enhance the phagocytic activity of AM [3] and mice that lacked SP-A exhibited a lower phagocytic activity and survival [10].
Because low levels of SP-A have been associated with neonatal disease (RDS, BPD) risk, as well as with risk in adult disease (IPF) or condition (lung trauma) [11], enhancing the expression of SP-A1, SP-A2, or both depending on the particular functional need may be another way to increase their levels in neonatal life. Although individuals with lung disease have been shown to have altered levels of SP-A, it is not known whether these reflect change in both gene products, or just one, and if the latter, which one. Given the functional differences between the two gene products and eventually functional differences among the variants of each gene, it is important to have a good understanding of the SP-A1 and SP-A2 gene-specific regulatory mechanisms in order to guide therapeutic decision making. Although differences in the regulation between SP-A1 and SP-A2 have been observed in organ cultures and in cell cultures, the details of the mechanisms are not fully understood [12]. Recent studies have implicated regulatory protein factors [30] and miRNAs [31] in the differential regulation of SP-A1 and SP-A2 expression. For example, some isoforms of the 14-3-3 family of proteins are specific for the translation of SP-A2, but not SP-A1 [30]. Whether these or other factors can in the future be used therapeutically to differentially regulate specific SP-A1 and SP-A2 expression remains to be determined.
In summary, serious consideration should be given to the question of whether SP-A1 and SP-A2, as well as SP-D (not discussed here in detail), should be included in surfactant replacement preparations or be given as an individual treatment. The mouse rescue experiment [1] discussed above for SP-A indicates feasibility and potentially a functional benefit to the AM as shown by changes in the cytoskeletal/ actin-related proteins. The cytoskeletal changes, as depicted in Figure, are central to several AM functions. Innate immunity, being the first line of defense, provides a logical target for therapy, because deranged innate immunity most likely leads to dire downstream consequences. Thus, ensuring a well-functioning AM is essential to lung health. SP-A1 and SP-A2 appear to be important regulators of AM protein expression and function, and using these therapeutically may help ameliorate disease severity in several conditions. Moreover, preliminary evidence indicates that SP-A1 and SP-A2 treatment may have a positive impact beyond innate immunity by benefiting surfactant-related functions, and perhaps clinical cases beyond RDS. Alternatively, understanding the regulatory mechanisms of SP-A1 and SP-A2 could help modulate SP-A1 and SP-A2 levels and therefore this line of investigation should be a research priority. In specific, such knowledge can help identify points of therapeutic intervention to enhance individual expression of SP-A1 and/or SP-A2 under certain conditions.


Physiological and Health-Related Adaptations to Low-Volume Interval Training: Influences of Nutrition and Sex

Interval training refers to the basic concept of alternating periods of relatively intense exercise with periods of lower-intensity effort or complete rest for recovery. Low-volume interval training refers to sessions that involve a relatively small total amount of exercise (i.e. ≤10 min of intense exercise), compared with traditional moderate-intensity continuous training (MICT) protocols that are generally reflected in public health guidelines. In an effort to standardize terminology, a classification scheme was recently proposed in which the term ‘high-intensity interval training’ (HIIT) be used to describe protocols in which the training stimulus is ‘near maximal’ or the target intensity is between 80 and 100 % of maximal heart rate, and ‘sprint interval training’ (SIT) be used for protocols that involve ‘all out’ or ‘supramaximal’ efforts, in which target intensities correspond to workloads greater than what is required to elicit 100 % of maximal oxygen uptake (VO2max). Both low-volume SIT and HIIT constitute relatively time-efficient training strategies to rapidly enhance the capacity for aerobic energy metabolism and elicit physiological remodeling that resembles changes normally associated with high-volume MICT. Short-term SIT and HIIT protocols have also been shown to improve health-related indices, including cardiorespiratory fitness and markers of glycemic control in both healthy individuals and those at risk for, or afflicted by, cardiometabolic diseases. Recent evidence from a limited number of studies has highlighted potential sex-based differences in the adaptive response to SIT in particular. It has also been suggested that specific nutritional interventions, in particular those that can augment muscle buffering capacity, such as sodium bicarbonate, may enhance the adaptive response to low-volume interval training.

Introduction
Interval training has long been considered an essential component of programs designed to maximize performance in highly-trained athletes, which typically involve a relatively high volume of submaximal, moderate-intensity continuous training (MICT) [1][2][3][4][5]. While less well-appreciated, interval training per se is a potent stimulus to induce physiological remodeling that resembles-or indeed may be superior to-changes typically associated with traditional endurance training [6][7][8][9]. This brief commentary focuses on physiological and health-related adaptations to low-volume interval training, which is characterized by sessions that involve a relatively small total amount of exercise, compared with MICT protocols that are generally reflected in current public health guidelines [10][11][12]. The present work builds upon recent reviews by some of the same authors [6,7,13] and also considers possible sexbased differences in the adaptive response to this type of training, in addition to the potential influence of nutritional manipulation on training outcomes. For a more comprehensive analyses of the physiological and health adaptations to interval training-and in particular comparisons between relatively high-volume interval training and traditional MICT, in which efforts are made to match energy expenditure-the reader is referred to recent reviews by others, including work that has focused on those at risk for, or afflicted by, cardiometabolic disorders such as cardiovascular disease and type 2 diabetes [8,[14][15][16][17][18]. Several other recent reviews have considered in detail various aspects of program design, with a particular focus on the application of interval training for athletic performance [19,20].

Characterizing the Training Stimulus: Standardizing Terminology
Interval training refers to the basic concept of alternating periods of relatively intense exercise with periods of lowerintensity effort or complete rest for recovery. A wide range of terms have been used by different groups to describe various interval training protocols, which has led to a dizzying array of acronyms and general lack of standardization in the literature. Weston et al. [8] recently proposed a simple classification scheme for interval training based on exercise intensity as part of an effort to standardize terminology in future studies. The authors suggested that the term 'high intensity interval training' (HIIT) be used to describe protocols in which the training stimulus is 'near maximal' or the target intensity is between 80 and 100 % of maximal heart rate (HR max ). In contrast, the authors advocated use of the term 'sprint interval training' (SIT) for protocols that involve 'all out' or 'supramaximal' efforts, in which target intensities correspond to workloads greater than what is required to elicit 100 % of maximal oxygen uptake (VO 2max ). Weston et al. [8] also suggested that the standardized term 'moderate-intensity continuous training' be used where appropriate in comparative studies. Other authors [21] have also recently considered various methodological approaches for the classification of interval training, including the use of turn-point or threshold models to prescribe intensity rather than percentages of HR max or VO 2max . We applaud the efforts to try and standardize interval training terminology research in future studies. While cognizant of the potential value in other approaches [21,22], especially for training prescription for athletes, we will employ the basic classification scheme proposed by Weston et al. [8] in the present review, given the widespread use of percentages of HR max and VO 2max to describe relative exercise intensity. Weston et al. [8] used the specific descriptors 'peak heart rate' and 'maximal oxygen uptake'; in the present review we will use 'HR max ' and 'VO 2max ' to describe relative intensities scaled to 'peak' and/or 'maximal' heart rate and oxygen uptake, respectively, for simplicity and consistency, and regardless of the specific term used in original studies that are cited here. There is no universal definition of what constitutes 'low volume' interval training, but in the present review we will consider protocols in which the total amount of intense exercise performed during a training session was B10 min within a training session, i.e. the summed total duration of the hard efforts, excluding the recovery periods and any warm-up or cool-down. Based on this depiction and the classification scheme proposed by Weston et al. [8], an example of a low-volume HIIT protocol is ten 60-s cycling efforts at an intensity that elicits *85-90 % HR max , interspersed by 60 s of recovery [23]. An example of low-volume SIT is the repeated Wingate Test model, which typically consists of four to six 30-s all-out efforts at mean power outputs corresponding to *250 % of the absolute workload elicited at the end of an incremental VO 2max , interspersed with a few minutes of recovery [24]. An overview of common protocols employed in interval training studies is depicted in Fig. 1.

Physiological Adaptations to Low-Volume Interval Training
It has been recognized for some time that relatively shortterm SIT and HIIT protocols can rapidly enhance the capacity for aerobic energy metabolism [25,26] and elicit physiological remodeling that resembles changes induced by MICT. While relatively few direct comparisons have  Fig. 1 Examples of protocols employed in interval training studies, expressed relative to PPO that is required to elicit VO 2max or VO 2peak . The figure shows typical MICT, e.g. 50 min at *35 % of PPO, which elicits *70 % of HR max (hatched box); low-volume HIIT, e.g. 10 9 1 min at a constant workload corresponding to *75 % of PPO, interspersed with 1 min of recovery, which elicits *85-90 % of HR max during the intervals (grey bars); and low-volume SIT, e.g. 4 9 30 s 'all out' effort at a variable power output corresponding to *175 % of PPO (averaged over the course of the intervals), interspersed with 4 min of recovery, which elicits *90-95 % of HR max during the intervals (black bars). Power output and heart rate estimates are derived from Little et al. [31] and Skelly et al. [60]. PPO, peak power output, VO 2max , maximal oxygen uptake, VO 2 peak, peak VO 2 , MICT, moderate-intensity continuous exercise, HR max , maximum heart rate, HIIT, high-intensity interval training, SIT, sprint-interval training been made, in one of the first studies to compare skeletal muscle adaptations after low-volume interval versus traditional endurance training, Gibala et al. [27] reported increases in various markers of mitochondrial content after only six sessions of SIT or MICT over 2 weeks. Young active men performed either four to six Wingate Tests with 4 min of recovery in between, or 90-120 min of continuous cycling at approximately 65 % VO 2max , per session. Total training time commitment was *2.5 h and *10.5 h for SIT and MICT, respectively, and total training volume based on mechanical work was * 90% lower in the SIT group (*630 vs. *6,500 kJ). Skeletal muscle needle biopsy samples obtained before and after training revealed similar increases in the maximal activities of citrate synthase and cytochrome c oxidase (COX) and the protein content of COX subunits II and IV, with no difference between groups [27]. Similar adaptations have been reported in studies that examined skeletal muscle adaptations to 2-week HIIT protocols [23,28]. Burgomaster et al. [29] compared two groups of previously sedentary individuals who performed either 6 weeks of Wingate-based SIT, 3 days/week similar to Gibala et al. [27], or MICT that involved 40-60 min of continuous cycling at 65 % of VO 2peak , 5 days/week. Both protocols elicited similar increases in the maximal activities of mitochondrial markers, including citrate synthase, pyruvate dehydrogenase and 3-hydroxyacyl CoA dehydrogenase, and also reduced muscle glycogen and phosphocreatine utilization during submaximal, matched-work exercise following training in both groups. The molecular mechanisms underlying skeletal muscle metabolic adaptations to low-volume interval training have been reviewed elsewhere [6], but in general many of the underlying signaling events appear to be at least qualitatively similar to processes proposed to regulate adaptations to MICT [31]. For example, similar acute activation of signaling pathways involved in mitochondrial biogenesis have been reported after a single session of SIT, HIIT, or MICT, including phosphorylation of 5 0 AMP (adenosine monophosphate)-activated protein kinase (AMPK), p38 mitogen-activated protein kinase (p38 MAPK), and p53 [31,32]. This suggests that at least some of the underlying mechanisms are qualitatively similar between the two training modalities, although it is also possible that interval training may stimulate pathways that initially differ from MICT but ultimately converge to elicit specific adaptive responses, e.g. mitochondrial biogenesis [3].
With respect to cardiovascular adaptations in healthy individuals, Rakobowchuk et al. [33] reported, in a companion paper that was based on the study by Burgomaster et al. [30], similar improvements in peripheral vascular structure and function, including popliteal artery distensibility and flow-mediated dilation, after 6 weeks of low-volume SIT and MICT. A subsequent study from another laboratory that employed the same experimental design [34] found that 6 weeks of SIT and MICT were equally effective in increasing skeletal muscle microvascular density and enzyme content, despite large differences in total training volume. Consistent with these findings, McKay et al. [35] reported that eight sessions of either SIT (eight to twelve 60-s intervals at 120 % VO 2max , separated by 60 s of rest) or MICT (90-120 min at 65 % VO 2max ) improved muscle O 2 utilization kinetics, suggestive of adaptations in local microvascular perfusion. Bailey et al. [36] also found that six sessions of Wingate-based SIT over 2 weeks accelerated muscle O 2 utilization kinetics; however, no improvement was seen after MICT. With regards to central adaptations, MacPherson et al. [37] found that cardiac output, based on an acetylene non-rebreathing technique, was increased after 6 weeks of MICT but not SIT, despite similar improvements in VO 2max . The authors suggested the early time course of cardiovascular adaptation to SIT and MICT may differ, with peripheral factors (i.e. enhanced O 2 extraction) being more important for the former. In support of this interpretation, Jacobs et al. [38] showed that 2 weeks of SIT increased VO 2max and skeletal muscle respiratory capacity, but not cardiac output based on a nitrous oxide rebreathing method. In contrast, Esfandiari et al. [39] recently reported that Doppler-derived measures of end-diastolic volume, stroke volume, and cardiac output, as well as blood volume and VO 2max , were increased to a similar extent after a 2-week HIT protocol that was modeled after Little et al. [29], as well as a highvolume MICT protocol. While additional work is warranted to clarify the precise nature and time course of the mechanisms involved, a substantive body of evidence suggests that low-volume SIT and HIIT protocols constitute relatively time-efficient training strategies to induce an array of physiological adaptations that resemble changes normally associated with high-volume MICT, at least over the short-term, i.e. up to several weeks.

Changes in Health-Related Indices After
Low-Volume Interval Training Cardiorespiratory fitness has been documented to be a stronger predictor of risk for adverse health outcomes than traditional risk factors such as hypertension, smoking, obesity, and hyperlipidemia [40]. As little as six sessions of low-volume SIT over 2 weeks has been shown to improve cardiorespiratory fitness, as reflected by increased VO 2max during an incremental exercise test to exhaustion [36,[41][42][43]. A recent systematic review and meta-analysis based on 16 studies summarized the improvements in cardiorespiratory fitness following SIT in young healthy individuals, and reported a moderate to large effect size in comparison to non-exercise control groups, and no difference when compared with MICT [44]. Interestingly, the effect of SIT on aerobic capacity was unaffected by initial fitness level (sedentary, recreational, trained), length of training intervention (\6 weeks, C6 weeks), or mode of training (cycling, running, rowing). The aggregate increase in VO 2max after SIT was 3.6 ml/kg/min (8 %), an improvement that would approximately translate into a 15 and 19 % lower risk of all-cause and cardiovascular disease mortality, respectively [45]. Similar to the findings of Gist et al. [44], another meta-analysis of 19 studies by Sloth and colleagues [46] reported that VO 2max increased by a range of 4-13 % after 2-8 weeks of SIT in healthy sedentary or recreationally active adults. Data from individual studies, reminiscent of classic work by Tabata et al. [27], reveal that a surprisingly small total SIT dose can elicit relatively large changes in VO 2max . For example, Ma et al. [47] recently showed that 16 sessions of a protocol that involved eight 20-s cycling efforts at 170 % VO 2max , interspersed with 10 s recovery, improved VO 2max in young men by 19 % after 4 weeks. Similar improvements have also been reported using protocols involving 10 s [41] and 20 s allout cycling sprints [48]. There are less data on the effects of low-volume HIIT but recent studies showed improvements in VO 2max in overweight women after 6 weeks of training [49], and in patients with coronary artery disease after 12 weeks of training [50], with the latter change being comparable to a similar period of MICT that involved twice as much exercise. Relative intensity appears to be important when it comes to HIIT protocols, with a recent study showing that cardiovascular adaptation, as reflected by change in VO 2max , was reduced when overweight/obese men trained using a 10 9 60-s protocol at an intensity equivalent to 70 % of peak power elicited at VO 2max compared with 100 % of peak power [51]. A few studies have reported improvements in glycemic control after short-term, low-volume interval training, in both healthy individuals and those at risk or afflicted by cardiometabolic diseases. Babraj et al. [52] were the first to report that six sessions of SIT over 2 weeks was a sufficient stimulus to improve insulin sensitivity in young active men, measured using oral glucose tolerance tests (OGTT). These findings were confirmed by Richards et al. [53], who showed that, using the hyperinsulinemic euglycemic clamp technique, insulin sensitivity was improved 72 h following a 2-week SIT intervention in healthy men and women. Whyte et al. [43] reported 2 weeks of SIT in overweight but otherwise healthy adults improved OGTT-derived estimates of insulin sensitivity when measured 24 but not 72 h after training, and Hood et al. [23] showed that six sessions of HIIT over 2 weeks improved insulin sensitivity based on fasting measures of glucose and insulin in previously sedentary individuals. Using continuous glucose monitoring (CGM), Little et al. [54] reported lower 24-h blood glucose concentration in patients with type 2 diabetes when measured 72 h following a 2-week HIIT protocol. All of these studies have been relatively short-term investigations on small numbers of subjects, without direct comparison with high-volume MICT protocols.
Recent evidence has also highlighted the potential for low-volume interval training to induce favorable changes in body composition. For example, 18 sessions of all-out running SIT over 6 weeks decreased whole body fat mass and increased whole body fat-free mass in recreationally active men [55] and women [56]. A cycling-based SIT protocol involving 60 repetitions of 8 s all-out sprints, interspersed with 12 s recovery, performed 39/week for 15 weeks, was also shown to be more effective than an MICT protocol involving 40 min of cycling at 60 % of VO 2max for decreasing whole body and abdominal fat mass in women [57]. Gillen et al. [49] also reported reductions in whole body and abdominal fat mass following 6 weeks of low-volume HIIT in overweight women. Boutcher [58] has discussed the various factors that could mediate changes in body composition after low-volume interval training, and some evidence has been presented in support of specific mechanisms, including increased post-exercise oxygen consumption or changes in appetite [59][60][61].

Potential Sex-Based Differences in the Adaptive
Response to Low-Volume Interval Training Recent evidence from a limited number of studies has highlighted potential sex-based differences in the adaptive response to SIT. Metcalfe et al. [48] utilized a protocol that involved two 20-s all-out sprints within a 10-min training session that otherwise consisted of low-intensity cycling, including warm-up and cool-down. When previously sedentary but otherwise healthy men and women trained 39/ week for 6 weeks, gains in aerobic capacity were similar, but insulin sensitivity measured using OGTTs was improved in men only. We also previously observed no change in OGTT-derived estimates of insulin sensitivity after a 6-week HIIT intervention in women [49], although this study did not involve a sex-based comparison. It has been suggested that high rates of glycogen breakdown and subsequent resynthesis following intense exercise may explain the rapid improvement in insulin sensitivity after SIT [48]. However, in comparison to men, women are reported to break down 42 % less muscle glycogen in type 1 fibers during a single Wingate sprint [62], which is supported by a lower blood lactate accumulation following single [63,64] and repeated 30-s sprints [64]. The reduced rate of glycogenolysis may be associated with lower basal activities of muscle phosphofructokinase [65] and lactate dehydrogenase reported in women [65,66], or a lower catecholamine response to repeated sprints [63,64]. Interestingly, women are suggested to have a greater predisposition for aerobic metabolism as estimates based on respiratory gas analyses suggest that the aerobic contribution to a 30-s sprint is 25 % higher in women compared with men [67]. This difference could also explain in part the relative glycogen sparing that has been observed in women [62], with potential effects of associated metabolic byproducts on downstream signaling events that regulate muscle adaptations. Divergent adaptations in skeletal muscle remodeling were reported following a 3-week SIT intervention in active young men and women. Oral administration of deuterium oxide revealed higher rates of muscle protein synthesis in men over the course of training in both the mixed and cytosolic fractions [68]. However, it is important to note that other studies involving mixed cohorts of men and women have not described sex-based differences in the adaptive response to interval training [23,29,53], although these studies were not specifically designed to address this issue. Clearly, additional wellcontrolled studies are warranted to determine whether women might in fact 'respond less' to low-volume SIT, using best practice designs that control for various factors, such as menstrual cycle phase and relative fitness, that can increase variance and lead to false conclusions regarding potential sex differences [69].
6 Can Nutrition Alter the Adaptive Response to Low-Volume Interval Training?
Based on our understanding of the molecular biology underlying muscle adaptation to exercise training [31], and the potential for nutrition to modulate training adaptation [70], interventions in theory could augment the adaptive response to interval training by: (1) improving energy metabolism during exercise, which could facilitate greater total work and an enhanced chronic training stimulus; or (2) promoting some aspect of the adaptive response during recovery, which could lead to enhanced physiological adaptations over time [71]. A large number of potential candidates, including, for example, caffeine and creatine, have been identified and discussed in detail elsewhere [72][73][74]. For the purposes of this review, only a few specific nutritional practices or supplements will be considered here.
Arguably the best evidence to date regarding the potential for nutritional manipulation to enhance physiological adaptation to interval training is research on carbohydrate (CHO) restriction protocols [75]. As originally proposed by Hansen et al. [76], the basic concept is that training in a CHO-restricted state and/or with reduced glycogen availability could serve to augment the acute molecular signaling response to exercise [76]. A typical research design involves a comparison of two groups who either train once daily, or twice a day, every other day, for up to several weeks, with the manipulation resulting in the latter performing approximately half of all training sessions in a 'reduced' state [77][78][79]. These studies have generally failed to show any beneficial effect on performance, at least using whole-body exercise protocols that resemble normal athletic competition, and indeed perception of effort may be increased. However, from a basic science standpoint, studies have shown that CHO-restricted training can enhance mitochondrial adaptation, even in highly trained individuals. This could result from the transient yet repeated enhancement of acute signaling proteins that regulate mitochondrial biogenesis. For example, several studies have shown that the acute activation of AMPK [80], p38-MAPK [81], and p53 [82] is amplified when interval training is commenced with low glycogen per se or reduced CHO availability. Specifically in regards to AMPK regulation, the enhanced signaling may be mediated through a greater liberation of the regulatory beta subunit, which is sequestered under normal glycogen conditions [83][84][85].
Interventions that alter buffering capacity may also be of particular relevance to interval training. Repeated sprints have the potential to depress intramuscular pH to 6.5-6.8 [86][87][88][89], which may reduce glycolytic flux [87,88] and alter calcium sensitivity/handling [90,91]. However, the extent to which pH may play a role in fatigue has been questioned [89,92,93]. Nonetheless, elevated buffering capacity has been associated with enhanced sprint ability [94] and short duration endurance cycling performance [95]. Hence, research has focused on supplementing the natural buffering system in an attempt to augment physiological adaptations and performance. One method of manipulating the extracellular buffering capacity is through ingestion of sodium bicarbonate (NaHCO 3 ), as the associated elevation of blood bicarbonate, pH and base excess has been proposed to elevate H ? efflux out of contracting muscles [96,97]. Another hypothesis is that alkalosis may help maintain muscle membrane excitability through improved strong ion regulation [98][99][100]. Regardless of the potential underlying mechanism, there is good evidence to support the practice of acute NaHCO 3 ingestion, with a recent meta-analysis finding that a dose of 0.3-0.5 g/kg body mass improved mean power output by 1.7 % (±2.0 %) during short high-intensity exercise [101]. However, it must be emphasized that not all studies have found performance improvements after NaHCO 3 ingestion, and individual responses are variable [102].
With respect to the evidence that repeatedly induced metabolic alkalosis can augment adaptations over the course of chronic training [103][104][105], Edge et al. [103] reported that recreationally active women who consumed NaHCO 3 for 8 weeks in conjunction with interval training experienced lower H ? accumulation during each session, and this was associated with a training-induced improvement in endurance capacity and lactate threshold. To garner insight into the potential mechanistic basis for the observed performance enhancement, Bishop and colleagues [105] had rats perform interval training five times/ week for 5 weeks while supplemented with NaHCO 3 or a placebo. Both groups increased endurance capacity, as evidenced by significant increases in running time to exhaustion in comparison to unexercised control rats. However, the rats supplemented with NaHCO 3 showed a superior performance improvement, attributed to greater improvements in both mitochondrial mass and respiration [104]. It is important to note that within both studies, groups were matched for total work performed during each training session, and thus the enhanced muscle adaptations and performance cannot be attributed to differences in total training volume.
Several studies have investigated the effects of NaHCO 3 on muscle metabolism during acute exercise and these provide additional insight into potential cellular mechanisms involved [96,97,[106][107][108]. A relatively common finding is that NaHCO 3 supplementation increases the rate of muscle glycogen degradation [96,97], and this is associated with increased content of lactate in muscle and/ a b Fig. 2 Hypothesized acute signaling mechanism underpinning enhanced training adaptations in response to chronic NaHCO 3 supplementation. a AMPK acts as an energy sensor that is activated by various signals generated during muscle contraction (e.g. increased AMP), which subsequently activates PGC-1a, leading to increased transcription of various genes involved in mitochondrial biogenesis. b Supplementation with NaHCO 3 may alter muscle metabolism, resulting in greater increases in AMP, which could enhance AMPK activation through interaction with the csubunit. Glycogen utilization during exercise is also increased after NaHCO 3 supplementation, and the AMPK b-subunit that is sequestered by glycogen may be liberated to a greater extent. Greater AMPK activation could result in greater downstream signaling, including activation of PGC-1a and increased gene expression. Red arrows depict potential mechanisms that are supported by experimental data, whereas question marks indicate areas that remain to be directly investigated. NaHCO 3 sodium bicarbonate, AMPK adenosine monophosphate kinase, PGC-1a peroxisome proliferatoractivated receptor c co-activator or blood [96,97,106,107]. Hollidge-Horvat et al. [96] also reported that exercise following NaHCO 3 supplementation resulted in elevated muscle content of adenosine diphosphate, adenosine monophosphate, and inorganic phosphate, while phosphocreatine content was reduced in comparison to placebo. The authors proposed that altered cellular energetics were due to higher glycogen utilization, facilitated by a lack of inhibition on glycolytic flux, which conversely reduced free fatty acid (FFA) metabolism [96]. In support of this interpretation, the authors also found a marked decline in free carnitine as well as muscle pH following supplementation. Both mechanisms have been implicated in the inhibition of carnitine palmitoyltransferase 1 (CPT-1), the rate-limiting enzyme of long-chain fatty acid transport into mitochondria for beta oxidation [109][110][111][112]. Hollidge-Horvat and colleagues further suggested that decreased FFA utilization would cause a decline in the ratio of reduced/oxidized nicotinamide adenine dinucletides in the mitochondria, requiring the observed alterations in cellular energetics to drive oxidative phosphorylation [96]. The hypothesized acute signaling mechanism underpinning enhanced training adaptations in response to chronic NaHCO 3 supplementation is depicted in Fig. 2.
It has also been speculated that nutritional manipulation of intramuscular buffering capacity could augment adaptations to interval training. The dipeptide carnosine is an important intramuscular buffer, and the intramuscular content can be increased through chronic oral supplementation with the rate-limiting amino acid precursor, b-alanine [113]. A recent meta-analysis suggests that b-alanine has ergogenic effects on exercise lasting 1-4 min with an improvement of 2.85 % in performance measures [114]. While the majority of studies have focused on performance, recent evidence suggests metabolism within the contracting muscle may be altered by b-alanine supplementation. For example Gross et al. [115] found that in response to a single, high-intensity, fixed-power, fixedduration test, supplementation with b-alanine appeared to reduce the oxygen deficit and accumulation of both blood and muscle lactate. The authors suggested that an enhancement in oxidative phosphorylation coinciding with a decrease in substrate level phosphorylation was evident [115]. Interestingly, these results appear to contrast those found when manipulating the extracellular buffer with NaHCO 3 supplementation, as discussed above. Aside from this initial work by Gross and colleagues, very little is known regarding other acute metabolic effects that may influence muscle signaling [115]. Recent investigations using relatively short training blocks lasting up to several weeks suggest that chronic b-alanine supplementation does not further enhance the adaptive response [115][116][117].
In summary, while some evidence suggests that specific nutritional interventions may alter the adaptive response to interval training, future work should focus on elucidating the underlying mechanisms as well as understanding how these may translate to increased performance during athletic competition.

Conclusions
The majority of low-volume interval training studies have utilized relatively short intervention periods (i.e. lasting up to several weeks) and future work involving long-term (i.e. months to years) interventions is needed to advance our basic understanding of how manipulating the exercise stimulus translates into physiological remodeling. From an applied perspective, there is value in trying to establish the minimum 'dose' of HIIT or SIT needed to stimulate meaningful improvements in clinical markers that are associated with disease risk. This is particularly germane given that 'lack of time' remains the most commonly cited barrier to regular exercise participation [118], and considering evidence that suggests that low-volume interval training is perceived to be more enjoyable than MICT [119]. There is also evidence that nutritional interventions can influence both acute and chronic adaptations to interval training [74], findings that may have relevance beyond athletic performance and competitive sport. As suggested by van Loon and Tipton [120], greater adaptation efficiency has clinical relevance, especially for individuals with severe exercise intolerance.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Biology Chemistry

text:
Identification and validation of p50 as the cellular target of eriocalyxin B

As an ent-kaurene diterpenoid isolated from Isodon eriocalyx var. Laxiflora, Eriocalyxin B (EriB) possesses potent bioactivity of antitumor and anti-autoimmune inflammation, which has been suggested to work through inhibition of NF-kappaB (NF-κB) signaling. However, the direct target of EriB remains elusive. In this study, we showed that EriB induced apoptosis is associated with the inhibition of NF-κB signaling in SMMC-7721 hepatocellular carcinoma cells. With activity-based probe profiling, we identified p50 protein as the direct target of EriB. We showed that cysteine 62 is the critical residue of p50 for EriB binding through the α, β-unsaturated ketones. As the result, EriB selectively blocks the binding between p50 and the response elements, whereas having no effect on the dimerization or the nuclear translocation of p50 and p65. SiRNA mediated knockdown of p50 attenuated the apoptosis induced by EriB in SMMC-7721 cells. Taken together, our studies illustrated that EriB induces cancer cell apoptosis through interfering with the binding between NF-κB and the response elements by targeting the cysteine 62 of p50, which highlights its potential for the development of p50 targeted cancer therapeutic agents.

Isolation of Eriocalyxin B and synthesis of the ABPs
Eriocalyxin B was isolated from leaves of isodon erioclyx var. laxiflora according to the reported method [1].
General information for chemistry: All reactions were performed under argon atmosphere using flamedried glassware unless otherwise noted. CH 2 Cl 2 and Et 3 N were distilled over CaH 2 . THF was distilled over sodium/ benzophenone ketyl. All reagents were commercially available and used without further purification unless indicated otherwise. Thin layer chromatographies were carried out on Qing-Dao silica plates (0.25 mm layer thickness). Flash chromatography was performed with 300-400 mesh silica gels. Yields reported were for isolated, spectroscopically pure compounds. 1 H and 13 C NMR experiments were performed on a Bruker AM-400 and DRX-500 NMR spectrometer at ambient temperature. The residual solvent protons ( 1 H) or the solvent carbons ( 13 C) were used as internal standards. 1 H-NMR data are presented as follows: chemical shift in ppm downfield from tetramethylsilane (multiplicity, coupling constant, integration). The following abbreviations are used in reporting NMR data: s, singlet; d, doublet; t, triplet; dd, doublet of doublets; dt, doublet of triplets; m, multiplet. EIMS and HREIMS were taken on a VG Auto Spec-3000 or on a Finnigan MAT 90 instrument. The synthetic schemes are shown as Figure S2.
Preparation of eriocalyxin-6-yl-homo succinic ester (2): To a solution of compound 1 (69 mg) and DMAP (10 mg) in DCM (1.5 mL) at 0°C was added Et 3 N (101 mg) and succine anhydride (30 mg) successively. The resulting mixture was slowly warmed to the room temperature and stirred for 15 hours until no starting material was detected. A HCl aqueous solution (1M) was added to quench the reaction. The aqueous phase was extracted with EtOAc (15 mL×3). The combined organic layers were washed with H 2 O and brine successively, [M+Na] + . The spectra data of compound 2 is identical to that described in the literature [2].
Preparation of 2-(2-azidoethoxy) ethanol (4): To a solution of polyethylene glycol (16.52 g) in THF (100 mL) was added Et 3 N (15 mL) dropwise. The resulting mixture was stirred at room temperature for 0.5 hour. Then the mixture was immersed in water-ice bath. And MsCl was added to the mixture dropwise. The mixture was slowly warmed to the room temperature, and stirred overnight. Then the solvent was evaporated off. EtOH (100 mL) and NaN 3 (6.5 g) was added successively. The mixture was heated to reflux for 24 hours. Then the solvent was evaporated off, and saturated NaCl aqueous solution was added to dilute the mixture. The aqueous phase was extracted with EtOAc (200 mL×3). The combined organic layers were washed with brine, dried over anhydrous Na 2 SO 4 and concentrated. The crude product was subjected to flash chromatography on silica gel (ethyl Supplementary Figure S2: Synthetic schemes of EBF 6, EBF7, EBB8. www.impactjournals.com/oncotarget/ acetate/petrol ether = 1: 3) to give compound 4 (17.02 g, 85%) as colorless oil. The structure of compound 4 was assigned by comparison the spectra data with that of the literature [3].
Preparation of 5-(dimethylamino)-N-(2-(2-hydroxyethoxy)ethyl)naphthalene-1-sulfonamide (DT5): step 1: To a solution of compound 4 (143 mg) and in MeOH (20 mL) under H 2 was added Pd/C (14 mg) in one portion. The mixture was stirred at room temperature for half an hour until no starting material was detected. The mixture was filtered through celite. The filtrate was concentrated under vacuum. The crude product was used for next step without purification.
Step 2: To a solution of the crude product (93 mg) and DMAP (5 mg) in THF (5 mL) was added Et 3 N (122 mg) dropwise. The resulting mixture was stirred at the room temperature for 0.5 hour. Then DNSCl (106 mg) was added to the mixture at 0 °C in two portions. The resulting mixture was further stirred for 4 hours until no starting material was detected by TLC. HCl aqueous solution (1 M) was added to quench the reaction. The aqueous phase was extracted with EtOAc (20 mL×3). The combined organic layers were washed with H 2 O and brine successively, dried over anhydrous Na 2 SO 4 and concentrated. The crude product was subjected to flash chromatography on silica gel (ethyl acetate/petrol ether = 1: 1.5) to give compound DT5 (99 mg, 71%) as green yellow film. The structure of DT5 was assigned by comparison the spectra data with that of the literature [4].
Preparation of 6-O-[5-(dimethylamino)-naphthalene-1-sulfonamide-N-2-ethyl-1-(1-ethoxyl)-2-hydroxyl]succinic ester-yl] Eriocalyxin B (EBF6): To a solution of compound 2 (11 mg) and DT5 (7 mg) in DCM (1.0 mL) at 0 °C was added EDCI (8 mg) and DMAP (5 mg) successively. The resulting mixture was slowly warmed to the room temperature and stirred for 5 hours until no starting material was detected. H 2 O was added to quench the reaction. The aqueous phase was extracted with EtOAc (10 mL×3). The combined organic layers were washed with brine, dried over anhydrous Na 2 SO 4 and concentrated. The crude product was subjected to flash chromatography on silica gel (Chloroform : MeOH = 30 : 1) to give EBF6 (17 mg, 85%) as green yellow foam. 1  The mixture was stirred at room temperature for 1 hour. Then compound 1 (17 mg) was added to the mixture. The resulting solution was stirred at room temperature for another 24 hours. And H 2 O was added to quench the reaction. The aqueous phase was extracted with EtOAc (10 mL×3). The combined organic layers were washed with brine, dried over anhydrous Na 2 SO 4 and concentrated. The crude product was subjected to flash chromatography on silica gel (Chloroform: MeOH = 30 : 1) to give EBB8 (20 mg, 76% brsm) as white powder. 1

Dansyl tagged EriB dominantly labeled a 50-kDa protein
The cytoplasmic fraction and the nucleic fraction of SMMC-7721 cell lysates were incubated with EBF6 (5 μΜ), with or without the presence of EriB, followed by resolving with SDS-PAGE and imaging under UV transllumitor ( Figure S3).

EriB selectively binds to p50 in HEK293T cells
HEK293T cell lysates pretreated with or without TNF-α were incubated with EBB8 in the absence or presence of EriB, or with biotin alone, followed by pulldown with streptavidin beads. The precipitates were resolved by SDS-PAGE, and the gel subjected to immunoblotting with p50 antibody, with β-actin as the input.

Liquid chromatography-mass spectra analysis
Liquid chromatography was performed on a nano Acquity UPLC system (Waters Corporation, Milford, USA) connected to a LTQ Orbitrap XL mass spectrometer (Thermo Scientific, Bremen, Germany) equipped with an online nano-electrospray ion source (Michrom Bioresources, Auburn, USA). Peptides were resuspended with 25 μL solvent A (5% acetonitrile, 0.1% formic acid in water). 20 μL peptide solution was loaded onto the Captrap Peptide column (2mm x 0.5mm, Michrom Bioresources, Auburn, USA) at a 20 μL/min flow rate of solvent A for 5 min and then was separated on a Magic C18AQ reverse phase column (100 μm id×15cm, Michrom Bioresources, Auburn, USA) with a linear gradient. Starting from 5% B (90% acetonitrile, 0.1% formic acid in water) to 45% B (in other words, from 95% A to 55% A, the same below) in 70 min. The column flow rate was maintained at 500 nL/min and column temperature was maintained at 35 °C. The electrospray voltage of 1.4 kV versus the inlet of the mass spectrometer was used.
LTQ Orbitrap XL mass spectrometer was operated in the data-dependent mode to switch automatically between MS and MS/MS acquisition. Survey full-scan MS spectra with one microscan (m/z 350-1800) was acquired in the Obitrap with a mass resolution of 100,000 at m/z 400, followed by MS/MS of the eight most-intense peptide ions in the LTQ analyzer. The automatic gain control (AGC) was set to 1000 000 ions, with maximum accumulation times of 500 ms. For MS/MS, we used an isolation window of 2 m/z and the automatic gain control (AGC) of LTQ was set to 20 000 ions, with maximum accumulation time of 120 ms. Single charge state was rejected and dynamic exclusion was used with two microscans in 15s and 30 s exclusion duration. For MS/MS, precursor ions were activated using 35% normalized collision energy at the default activation q of 0.25 and an activation time of 30 ms. The spectrum were recorded with Xcalibur (version 2.0.7) software.
The mass spectra were searched using the Mascot Daemon software (Version 2.3.0, Matrix Science, London, UK) based on the Mascot algorithm. The database used to search was the protein NFKB1 (P19838). The searching parameters were set up as follows: full trypsin (KR) cleavage with two missed cleavage was considered. Oxidation on methionine and Eriocalyxin B of the Cys