While many people have great affection for southern hairy-nosed wombats, they are also considered by others to be an agricultural pest, because of the damage they can cause to farmland and agricultural infrastructure. Therefore, we need to have a good understanding of how many wombats there might be and how the population is changing, if we are to make properly informed decisions on how to best manage them. Unfortunately, because wombats are nocturnal and live underground, and because they use a number of different burrows throughout their home ranges, counting them can be difficult. We used motion-activated cameras to record how often wombats use each burrow in order to develop a reliable method of counting wombats that we can apply at the broad scale. We found that, on average, there are around 0.43 wombats for each active burrow. The use of video cameras to record this information provided a much simpler and less invasive means of researching wombat behaviour than methods such as trapping. However, video cameras do have limitations that need to be considered, and researchers need to fully understand their capabilities and limitations before employing them in the field.Broad-scale abundance estimates of the southern hairy-nosed wombat population use a proxy measure based on counting the number of active burrows, which is multiplied by an index of ‘wombats/active burrow’. However, the extant indices were calculated in the 1980s, prior to the use of calicivirus to control rabbits, and used invasive monitoring methods which may have affected the results. We hypothesise that the use of video might provide a logistically simple, non-invasive means of calculating updated indices. To this end, motion-activated, infra-red still and video cameras were placed at various distances outside active wombat burrows in the South Australian Murraylands and Eyre Peninsula regions. The captured imagery was inspected to determine how often the burrow was occupied by one or more wombats, and how effective the cameras were at detecting wombat activity. Video data was clearly superior to the still imagery, with more than twice as many burrow occupancies being positively identified (still: 43%). The indices of wombats/active burrow calculated based on video imagery were: Murraylands: 0.43, Eyre Peninsula: 0.42. 1948 false positive videos were recorded, of which 1674 (86%) occurred between noon and sunset. Lasiorhinus latifrons) inhabit a fragmented distribution across the semi-arid regions of south-central South Australia and the south-eastern corner of Western Australia , a more accurate assessment of the number of wombats/active burrow can be obtained by determining the proportion of active burrows which are being simultaneously occupied by wombats . To achieve this, a reliable method of determining when wombats enter and exit each burrow, and how many wombats are using the burrow at the same time, is required; one which does so non-invasively to minimise any changes in the animals’ behaviour.Motion-activated infra-red cameras (camera traps/wildlife trail cameras) offer a relatively cheap and logistically simple means of monitoring wildlife behaviour . The useThe aims of this study were to compare the effectiveness of video and still imagery for determining how often the active burrows of southern hairy nosed wombats are utilised, and to use video and still imagery to calculate an index of the number of wombats/active burrow based on burrow occupancy rates.This study was conducted in two phases. Phase one was conducted in the Murraylands region of South Australia in late spring/early summer 2017. The results from Phase one were analysed and used to refine the camera settings for the Phase two, which was conducted on the Eyre Peninsula during autumn 2018.Phase 1 was conducted in the South Australian Murraylands region at two locations—the Moorunde Wildlife Reserve  and the Brookfield Conservation Park —from 17 October to 12 November, and 15 November to 10 December 2017 respectively. Five active wombat burrows were selected at each location  . BurrowsThe still camera was configured to capture three x five-megapixel images (2592 × 1944 pixels) each time the camera was triggered, with a pause of five seconds between image sequences. These settings were the maximum number of images per sequence and the shortest pause time available on the camera. The video camera was configured to take a one-minute 720 P video (1280 × 720 pixels) each time the camera was triggered, with a pause of five seconds between subsequent recordings. The manufacturer’s claimed triggering speed of the cameras was 0.6 s.The first two days of imagery from each location were discarded to reduce any potential bias in the wombats’ behaviour which may have been caused by disturbance during the installation of the cameras . As wombThe time and date of all the images and videos which contained wombats and all false positive videos were then noted and collated. We then examined all the wombat images and videos to determine whether we could positively identify a wombat entering or exiting a burrow, or whether they showed other activity unrelated to burrow entry/exit. We also examined the imagery to determine whether the burrow was being occupied by more than one wombat simultaneously. Only adult wombats were counted; joeys were excluded from our calculations. As wombats are nocturnal, we would generally expect them to exit the burrow in the late afternoon/evening, potentially visit other burrows during their active period or re-enter their original burrow across the night and then finally re-enter a burrow in the early morning where they would shelter during the day. We therefore considered a burrow to be occupied if there was evidence of a wombat entering the burrow in the morning and remaining inside during the middle of the day. The results were collated by camera pairings (close-up versus medium-range versus long-range) and by video versus still cameras.All data was collated on a Microsoft Excel spreadsheet (2013 version 15), and statistical tests were conducted using the ‘Data Analysis’ tools add-in. The ‘Burrow Occupation Rate’ for each burrow was calculated by the dividing the number of days each burrow was occupied by one or more wombats by the number of valid observation days for that burrow. The ‘Wombat Occupancy Rate’ was calculated in the same manner as the ‘Burrow Occupancy Rate’, but was adjusted to take into account days when the burrow was occupied by more than one wombat simultaneously. The overall occupancy rate for each survey location was calculated by pooling the data for all burrows at that location, to account for any variations in the number of observation days per burrow. The ‘false positives’ for all video cameras were pooled and collated by time of day when they occurred.Data from the camera positions (close vs. medium vs. long-range) and camera types (video vs. still) were compared using a non-parametric test for related samples. The data was initially checked for normality (skewness and kurtosis), then analysed using the Wilcoxon signed-rank test for two related samples.Phase 2 was conducted at the Dakalanta Conservation Park  on the Eyre Peninsula of South Australia, from 10 May to 7 June 2018. Ten active wombat burrows were selected for monitoring .Only the close and medium range video cameras were used; the long-range cameras and the still cameras were dispensed with. The camera settings were changed from those used during phase one to reduce the resolution of the video from 720 P to 320 × 240 pixels. The cameras were also set to revert to standby mode between 10:30 and 14:30 h each day, with no video recorded during that time. A single still camera was also mounted on the same pole as the ‘medium’ video camera, and was set to capture imagery between 10:00–15:00 each day . This camera was used solely to confirm that no animals had left the warrens whilst the video cameras were in standby mode. The same analysis methodology that was used during phase one was also used during this phase, except that the analysis of false positives was not conducted at this site.Although we installed cameras at five burrow sites in both locations in the Murraylands , all six cameras at one site (Brookfield site #5) did not operate as they were not switched on correctly (set to ‘test’ instead of ‘on’). Of the nine remaining sites (54 cameras), ten video cameras stopped recording before the end of the survey period due to the data storage capacity (32 Gb) being reached .In total over 15,000 still images and videos were captured for analysis, of which 509 videos and 948 still images were of wombat activity. There were 1948 false positive videos which did not appear to have any obvious triggering event within the field of view.p = 0.042). The distance at which the cameras were installed from the burrow entrance also affected our ability to identify whether a burrow was occupied. The cameras situated close to the burrow entrance successfully identified that a burrow was occupied on 71/92 occasions (77%) versus 60/92 for the medium-range cameras (65%) and 23/92 (25%) for the long-range cameras. A Wilcoxon signed-rank test showed that there was no significant difference between the close-up and the medium-range cameras , but there was a significant reduction in our ability to positively confirm burrow occupancy from images derived from the long-range cameras   from the still imagery  .Eight out of nine of the burrows for which we had data were occupied by a wombat or wombats at some time during the survey period. The occupancy rate varied from 0% (burrow assessed as active but not occupied at any time during the survey period) to 88% (burrow occupied for 22/25 days). Of the eight burrows which were occupied, two were occupied for less than 25% of the time (12% and 24%), two were occupied for 25–50% of the time (32% and 40%), three were occupied for 50–75% of the time , and one was occupied for more than 75% of the time (88%). Two burrows (Moorunde sites #4 and #5), were occupied by two wombats simultaneously for a total of two and three days respectively  Table 2Table 2.The burrow occupancy rate—the proportion of burrows which were occupied at any one time—during this phase of the study was 0.41 (SD = 0.26). The wombat occupancy rate, and hence the index of wombats/active burrow for the Murraylands, was 0.43 (SD = 0.29).Of the 1948 false positive videos, 1464 were from Moorunde and 484 were from Brookfield. 1674 of the false positive videos (86%) occurred in the afternoon between 12:00 and 18:00, with only 27 (2%) occurring at night between 20:00 and 06:00 .Although we installed cameras on ten burrows, the cameras on one burrow (site #4) were dislodged by a herd of deer after six days of operation, leaving only four days of valid observations. This site was therefore discarded from further analysis. A second set of cameras (site #10) was also dislodged by the deer after 14 days of operation, but as this provided 12 days of data this site was included in our analysis. Seven of the remaining eight sites provided a full 25 days of data for analysis, with the data storage capacity of the cameras at the remaining site (site #2) being filled after 20 days .Eight out of nine burrows for which we had valid data were occupied by a wombat or wombats at some time during the survey period. The burrow usage rate—the proportion of days when the burrow was in use by one or more wombats—varied from 0% (site #1: burrow assessed as active but not occupied at any time during the survey period) to 100% (site #2: burrow occupied every day during the survey period). Of the eight burrows which were occupied, two were occupied for less than 25% of the time (both at 8%), four were occupied for 25–50% of the time , none were occupied for 50–75% of the time, and two were occupied for more than 75% of the time (76% and 100%) . Two burThe mean burrow occupancy rate—the proportion of burrows which were occupied at any one time—during this phase of the study was 0.35 (SD = 0.33). The overall wombat occupancy rate—the mean number of wombats/active burrow—for the Eyre Peninsula, was 0.42 (SD = 0.54).This study informs two important areas of wombat population research; the reliability of cameras as tools for monitoring wombat activity, and the calculation of an index of the number of wombats/active burrow for use in population abundance estimates. Our results provide evidence for the efficacy of video as a tool for determining warren occupancy rates, albeit with some limitations. They also provide lessons in regard to understanding how the cameras work, and ensuring that they are properly sited and the correct settings are used.Comparisons between the video and still imagery collected during phase one of this study indicated that there was a clear difference in our ability to positively identify wombat burrow occupancy from video versus the still imagery. The identification of burrow occupancy from video was relatively simple, whilst the approach used in previous studies of identifying individual wombats from still imagery can be difficult and time consuming, with identification relying on characteristics  that are not always visible in the imagery. Further, because wombats do not just reside in one warren, but rather use up to ten different warrens throughout their home range , accountThe failure of the long-range cameras to contribute much useful information during phase one of the study (25% of burrow occupancies identified) highlights some of the limitations with using cameras for this type of research . There wThe Passive Infra-Red (PIR) sensors used on these cameras detect the surface temperature of objects in the field of view, and trigger the camera when a change in temperature is detected in part or all of the sensor . This ocWhilst previous studies have suggested that these false positives may be triggered by the wind moving vegetation within the field-of-view of the camera , our resThe high rate of false positives, coupled with the data requirements of high-definition (720 P) video, meant that we used up the data storage capacity (32 Gb) of some of the video cameras before the end of the planned survey period during phase one of the study. As a result, we reduced the resolution of the videos to the minimum size possible on the cameras (320 × 480 P) to reduce the data storage requirements for phase two of the study. While this largely solved the problem of data capacity, the high volume of wombat traffic at one site  still resulted in the data capacity of the cameras at that site being used up after 20 days. This highlights the need to carefully evaluate the potential volume of data which may be captured by a camera and the data storage capacity available, and to adjust the camera settings, survey periods and logistics of any study to ensure that data is not missed as a result of inadequate data storage capacity.In regard to the siting of the cameras around warrens, in the case of a wombat emerging from its burrow there would be only a limited aspect change in relation to the camera oriented directly into the burrow . The surface temperature of the wombat’s body is also likely to be similar to the ambient temperature of the burrow, especially when the wombat is covered in dirt and the weather is warm. This suggests that fossorial species such as wombats may represent a poor target for PIR detection. There was evidence for this in our observations of burrow entry/exit. Although we generally observed the entire burrow entry process from the video , in the case of burrow exits the camera usually did not trigger until the wombat had completely emerged from the burrow and was climbing out of the crater . We also noted cases where imagery of a wombat exiting the burrow would be captured on the medium-range camera, which was oriented side-on to the burrow entrance, but no imagery was captured on the close-up camera . This phWhether the failure of some of our cameras to detect wombat activity which was occurring within their field of view—and which was captured on other cameras with a different orientation to the target—is an inherent limitation of wildlife trail cameras, or whether it is a limitation of these type of cheaper, generic cameras which are entering the market is difficult to tell from our data. In either case, our findings provide strong support for the importance of understanding the capabilities and limitations of motion-activated infra-red cameras in general, and of the model of camera being used, prior to their use in studies of this type. It also underscores the importance of the correct placement and alignment of the camera in relation to the target and to minimise the potential for false triggers to occur . UnfortuIn regard to our calculation of the number of wombats/active burrow, our figure of 0.43 for the Murraylands is virtually identical to previous figures calculated for the region of 0.43 , 0.4389 Whilst other studies suggest that a range of indices are required for different conditions such as soil type, especially for small-scale population estimates in areas with a large number of calcrete warrens ,20, the Our results also highlight the difficulties with accurately assessing whether a burrow is active, an issue which has been previously identified in multiple studies ,13,22. TWhether these inaccuracies in the subjective assessment of a burrow’s active status constitutes a problem depends upon the context. Certainly, at the local scale, if research effort is spent on a burrow which is not active, then that effort may be wasted. Conversely, as the calculated indices of the number of wombats/active burrow are all based on subjective assessments which also includes the misidentification of the status of some burrows ,5,6,13, We also noted days where no wombat activity was captured on the cameras—and hence, we did not observe a wombat entering or exiting the burrow—but we assessed that the burrow was occupied. This can be explained by the observation of a wombat entering the burrow but not emerging until several days later. We noted three instances of a wombat remaining in its burrow for more than one day, with the longest period being three and a half days (wombat entered at 05:07 on 29 November and did not emerge until 21:29 on 2 December). A second wombat also did not emerge from a different burrow for two days during the same period. This was most likely related to the weather, with our cameras recording maximum temperatures in excess of 40 °C on both 29 and 30 November 2017. A herd of feral goats was also observed grazing on the surface of the warren on the evening of the 30 November . This avIn regard to burrow sharing by more than one wombat, while this is not thought to be common, it does occur, especially in areas dominated by layers of sheet calcrete limestone  where acWith studies of this nature there is always the possibility that the cameras did not capture all the wombat activity, Although the number of cameras that we used reduces the likelihood of this occurring, we cannot discount the possibility that we may have missed one or more burrow occupancies. As a consequence, our indices of 0.43 for the Murraylands and 0.42 for the Eyre Peninsula should be considered to be minimum figures, and further research should be undertaken to verify these findings.The use of motion-activated wildlife cameras has become more prevalent over the past 20 years, but there is still a great deal that researchers can and should learn about their capabilities and limitations, if they are to gain the maximum benefit from their use. Some of our results surprised us, especially when we observed wombat activity on one camera but saw nothing on another camera that had the same focal area covered. We, therefore recommend that pre-survey trials be undertaken before using cameras in the field to ensure their capabilities and limitations are fully understood, and camera settings, siting and alignment to the target are optimised. The use of multiple cameras with different positions and alignments should also be considered to overcome any potential limitations inherent in a single camera design. For surveys involving fossorial species we recommend that cameras be oriented at an angle to, rather looking directly into, the burrow.We found that it was much easier to determine wombat behaviour and burrow occupancy rates from video than still imagery, and we recommend the greater use of video for studies of this nature.The index of wombats/active burrow that we calculated (0.43) for the Murraylands was identical to previous studies for the region, whilst the index calculated for the Eyre Peninsula (0.42) was virtually identical. This suggests that these figures are probably robust enough for most broad-scale wombat population studies. However, we recommend that on-going studies of this nature be undertaken to refine our understanding of southern hairy-nosed wombat burrow occupation rates at different spatial scales and under different environmental conditions.


ROS are mainly produced as by-products during oxidative phosphorylation in mitochondria. Electron transport chain complex I generates superoxide ions toward the matrix side whereas complex III generates superoxide ions toward both the matrix and inter-membrane space. Superoxide ions are then converted into hydrogen peroxide (H2O2) by superoxide dismutase (SOD) and subsequently transformed into H2O by glutathione peroxidase. ROS play a key role in regulating numerous cellular processes, including cell growth and differentiation, phagocytosis and cell death. Thus, cellular ROS level is tightly controlled by ‘redox homeostasis’, which achieves balance by controlling ROS level through elimination via anti-oxidants i) [2+]i that coincides with increased activity of the Ca2+-dependent calcineurin, and subsequent DRP1 at S637 dephosphorylation that stimulates mitochondrial fission i) . In brea fission . While Cng cells , the facCytochrome C release and subsequent caspase activation and cell death could also result from prolonged mPTP opening and, indeed, cells depleted of Cdk5 showed increased activation of caspase-3 and -9 and apoptosis. Since apoptosis induced by Cdk5 loss is completely reversed by CsA and SfA and close to be fully inhibited by Mito-Tempo but unaffected by the Mdivi-1 inhibitor of mitochondrial fission, it appears that apoptosis is mediated via an mPTP-dependent mechanism and primarily through ROS increase  inhibitors  and bortsynthase .


The behaviors of and mechanisms acting in Ti–6Al–4V alloy during low-temperature superplastic deformation were systematically studied by using a Gleeble-3800 thermocompression simulation machine. Focusing on the mechanical behaviors and microstructure evolution laws during low-temperature superplastic compression tests, we clarified the changing laws of the strain rate sensitivity index, activation energy of deformation, and grain index at varying strain rates and temperatures. Hot working images based on the dynamic material model and the deformation mechanism maps involving dislocation quantity were plotted on the basis of PRASAD instability criteria. The low-temperature superplastic compression-forming technique zone and the rheological instability zone of Ti–6Al–4V were analyzed by using hot processing theories. The dislocation evolution laws and deformation mechanisms of the grain size with Burgers vector compensation and the rheological stress with modulus compensation during the low-temperature superplastic compression of Ti–6Al–4V were predicted by using deformation mechanism maps. Ti–6Al–4V, which is characterized by formability, biocompatibility, toughness, low density, high strength, anti-corrosion, and excellent high-temperature properties, is the most widely used Ti alloy both commercially and industrially . Due to Titanium alloys, especially the rudder surface of air-to-underwater missiles that are widely used in aerospace, hardly deform at room temperature. The superplastic temperature of materials is generally above half of the melting point, and the strain rate must be within an appropriate range. The largest elongation of superplastic alloys is at least 100% and is reportedly more than 2000% in some alloys . HoweverSuperplastic deformation mechanisms are classified by three major processes. These include dominant grain boundary sliding, compatible diffusional creep, and dislocation creep ,9. SuperIn this work, the low-temperature deformation of Ti–6Al–4V was investigated by using the flow curves detected from compression trials at varying tensile temperatures and strain rates. A new deformation mechanism map and a processing map of variable rheological instability concerning dislocation quantity were drawn for the two-phase Ti alloy. These were used to forecast the deformation mechanism and to quantify the dislocation quantity. This work can theoretically underlie the utilization of low-temperature deformation maps of Ti–6Al–4V .−4–0.05 s−1. Three samples per condition and each specimen were deformed to a real strain of 0.6 and then immediately water-cooled to ambient temperature [Multidirectional forging Ti–6Al–4V sheets in bar diameter of 50 mm were selected. The gauge part of each specimen was 12 mm long and 8 mm in diameter . The expperature ,26.2O containing 20 mL of HF and 40 mL of HNO3, and then observed using a LEICA Q550IW optical microscope . The average particle size and volume fraction of the β phase were detected on an OLYMPUS M3 image-meter . The microstructures were characterized on a Tecnai G2 20 transmission electron microscope  after mechanical grinding, punching, and twin-jet chemical polishing in an electrolyte of 5% HCLO4, 35% C4H9OH, and 60% CH3OH at a voltage of 20 V at 25 °C.In the metallographic tests, each specimen was polished mechanically, etched in 100 mL of HThe microstructure of the initial multidirectional forging of Ti–6Al–4V consisted of the scattered α phase (dark contrast) and the band-structured β phase (bright contrast) . The vol−1 (−1), the upper yield effect occurred.The deformation is nonuniform, and the deformed specimen is barrel-shaped due to the inevitable interfacial friction between the tested specimen and dies. Essentially, the computed flow stress–strain plots overestimate the real ones. For these reasons, the impact of friction on flow stress must be taken into account, which makes the stress–strain curves closer to the real ones. The details of flow stress correction have previously been reported ,28. The −1 a–d. The −1 a–d. At t−1 c,d. This−1) was selected for analysis , and when the strain ε was close to 0.6, it started to reached the stable state (zone III). The softening effect of this alloy during high-temperature deformation fell within the strain of ε = 0.14–0.57. Based on the above method, the strain ranges of the softening effect at different strain rates to reach the alloy temperature of 860 °C have been summarized in The rheological strain curve under the typical thermal deformation conditions σ=kεnQ  kJ/mol  kJ/mol . Q elevaThe activation energy of thermal deformation of Ti–6Al–4V is far larger than the activation energy for self-diffusion cited in the literature . This wad is average grain size; L is the linear intercept of metallopraphical microstructures. −4, 10−3, 5 × 10−3, and 5 × 10−2 s−1. Based on Equation (4) and The microstructure evolution rules of metal materials during high-temperature deformation considerably affect the hot forming properties. The grain size was computed as follows : (4)d=1.d is the grain size, σ is the stress, p is the grain index, 0D is the diffusion coefficient, b is the Burgers vector, G is the shear module, k is the Boltzmann constant, and R is the ideal gas constant. The Arrhenius constitutive relation universal model  was exprp, which reflects the effect of grain size on the thermoforming performance. The grain index at 860 °C is 2.31. With the above method, the p of this alloy at other temperatures can be determined  and dissipation assisting energy (J). The consumed energy or dissipation energy (G) is mostly converted to thermal energy and slightly stored as crystal defect energy in the material. The dissipated energy, resulting from structural changes during deformation, is called the assisting dissipation energy (J).According to the dynamic materialogic model, the plastic history of this material can be regarded as an energy dissipative system, and the energy dissipation is decided by the material processing rheological behaviors and obeys the power-law Equation : (6)σ=k×J and G is decided by the material rheological properties, and the J to G ratio is called the strain rate sensitivity index : The allocation between T) and strain (ε): At given temperature  and (11), the expression of power dissipation rate  and (14), we plotted the power dissipation rate and rheological instability of Ti–6Al–4V during thermal compression and thereby acquired the thermal processing maps . The cha−1, and the thermal deformation falls within the rheological instability zone , which does not fall within the instability zone. Thus, Ti–6Al–4V has very high thermal forming performance at low-temperature and low-strain-rate areas and at medium-temperature and medium-strain-rate areas. The strain rate of this alloy within 800–840 °C is 0.034–0.05 sity zone . The strSevere dislocation motion occurred during the thermal deformation of Ti–6Al–4V. Therefore, based on the Ruano–Wadsworth–Sherby (RWS) deformation mechanism, we introduced the dislocation model via a constitutive equation and plotting deformation mechanism maps that involved the dislocation quantity, grain size, strain rate, and rheological stress. m, and p are material constants, E is Young’s modulus, b is Burgers vector, D is the diffusion index, including the lattice index LD and the crystal boundary index gbD. The high-temperature deformation of metals can be described by a constitutive equation : (15)ε˙iThe internal dislocation root count of single crystal grains ( follows : (16)ni=d/b) × 10−7) and the normalized flow stress with modulus normalization ((σ/E) × 104) of Ti–6Al–4V at the above temperatures were calculated (The RWS deformation mechanism maps involving dislocation count at 830 or 890 °C were drawn in lculated . 7) (6.85 × 108) (52) (71) (368) dislocation polygon zone. The mechanism was the dislocation glide controlled by lattice diffusion, with a stress index of 7 (7)  (5425) (5816) (368) dislocation polygon zone, and the mechanism was the dislocation glide controlled by lattice diffusion with a stress index of 5. At 830 °C and a very high strain rate, Ti–6Al–4V fell within the (3.95 × 10dex of 7 . As the 6)  (6488) (4258) (415) dislocation polygon zone  The m of Ti–6Al–4V at 800–890 °C with a strain rate of 5 × 10−1; 860–875 °C and strain rate at 0.001–0.005 s−1; the rheological instability zone was at 800–840 °C and strain rate at 0.034–0.05 s−1. (2) The dynamic deformation mechanism map (DMM) thermal processing showed the machine-shaping of Ti–6Al–4V as follows: 800–840 °C and strain rate at 0.0005–0.001 s(3) The deformation mechanism of RWS Ti–6Al–4V involving dislocation count was clarified. The dislocation quantitative relationship of this alloy based on the modulus compensation stress and Burgers vector compensation was determined, and the low-temperature superplastic compression deformation mechanism was predicted.


Chara braunii, Marchantia polymorpha, Physcomitrella patens, Azolla filiculoides, and Salvinia cucullata) have been analyzed, and annotated genome sequences have become accessible. We searched 38 plant genome sequences including core eudicots, monocots, gymnosperms, fern, lycophytes, bryophytes, charophytes, chlorophytes, glaucophytes, and rhodophytes for lectin motifs, performed an extensive comparative analysis of lectin domain architectures, and determined the phylogenetic and evolutionary history of lectins in the plant lineage. In conclusion, we describe the conservation of particular domains in plant lectin sequences obtained from algae to higher plants. The strong conservation of several lectin motifs highlights their significance for plants.Lectins are a large and diverse class of proteins, found in all kingdoms of life. Plants are known to express different types of carbohydrate-binding proteins, each containing at least one particular lectin domain which enables them to specifically recognize and bind carbohydrate structures. The group of plant lectins is heterogeneous in terms of structure, biological activity and function. Lectins control various aspects of plant development and defense. Some lectins facilitate recognition of exogenous danger signals or play a role in endogenous signaling pathways, while others are considered as storage proteins or involved in symbiotic relationships. In this study, we revisit the origin of the different plant lectin families in view of the recently reshaped tree of life. Due to new genomic sampling of previously unknown microbial lineages, the tree of life has expanded and was reshaped multiple times. In addition, more plant genomes especially from basal Phragmoplastophyta, bryophytes, and Salviniales (e.g.,  After the discovery of the Archaea, a model was proposed that divides cellular life into three evolutionary domains: “Eukarya,” “Bacteria,” and “Archaea” . In thisArabidopsis, rice, soybean, and cucumber) points to a dynamic evolution of these protein families , a close sister group to angiosperms, was published    can furtSince substantial progress has been made recently in resolving the placement of eukaryotes within the Archaea, the primary focus of our study relates to the origin of plant lectins in the tree of life. We attempted to reconstruct the evolutionary origins of the plant lectin families. Our data highlight that some families are a eukaryotic innovation, while others are descendants of ancient protein families as they are also found in prokaryotes. We also considered the domain architectures and diversification of specific lectin families, with emphasis on the similarities/differences between land plant lineages and in lineages that are sister to land plants.Agaricus bisporus agglutinin, amaranthin, cyanovirin, Euonymus-related lectin (EUL), Galanthus nivalis lectin (GNA), hevein, jacalin, legume lectin, LysM: lysin motif, Nicotiana tabacum agglutinin (Nictaba) and ricin B], together with the malectin family -initially reported in Metazoa , five monocots , one basal angiosperm (Amborella trichopoda), two gymnosperms (Ginkgo biloba and Picea abies), two Polypodiopsida , one lycophyte (Selaginella moellendorffii), three bryophytes , one Charophyceae (Chara braunii), one Klebsormidiophyceae (Klebsormidium nitens), two core chlorophytes (Chlorella NC64A and Chlamydomonas reinhardtii), two prasinophytes (Ostreococcus lucimarinus and Micromonas sp. RCC299), one glaucophyte (Cyanophora paradoxa) and two rhodophytes . Exploration of the plant comparative genomics platform PLAZA 4.01 (Agaricus bisporus agglutinin), IPR008998 (amaranthin), IPR011058 (cyanovirin), IPR001480 (GNA), IPR001002 (hevein), IPR001229 , IPR001220 (legume lectin), IPR018392 (LysM), IPR024788 and IPR021720 , IPR025886 (Nictaba), and IPR000772 (ricin B). The domain architecture of the retrieved sequences was analyzed using the Interpro, incorporated in the PLAZA 4.0 toolbox. Because EUL and ricin B lectin domains are characterized by the same identifier, the extent of the EUL family was estimated based on the results from 2  was verified with Interpro 71.0 at https://www.ebi.ac.uk/interpro/ , PLAZA 4.0 (see footnote 1), Gymno PLAZA 1.02 . Multiple sequence alignments were performed online with MAFFT version 711 using default settings  were screened for the presence of plant lectin domains . It is cAgaricus bisporus agglutinin originates from fungi and data shown in Agaricus bisporus agglutinin homologs. In plants, the presence of this lectin domain is restricted to the bryophytes  and scattered over different families but is certainly not ubiquitous . This taMarchantia polymorpha was not yet available  including the bryophyte lineage, but unlike the amaranthins, are omnipresent. Presumably, this protein domain arose in the last common ancestor of the Embryophyta  and remavailable . A strikvailable  while hovailable , originaPorphyra umbilicalis, while GNA, LysM, ricin B and legume lectins homologs appear to be ubiquitous in Viridiplantae, including Chlorophyta and Streptophyta  in Salvinia cucullata. GNA homologs appear as a large fraction of the total number of lectin genes in Marchantia polymorpha, Physcomitrella patens and Picea abies but are a rather small family in Chlamydomonas reinhardtii, Klebsormidium nitens, and Ginkgo biloba. The size of the hevein family is very much dependent on the plant species, analogously to GNA homologs. Lectin homologs belonging to the jacalin and LysM family represent more than 70% of the total number of lectin genes in the chlorophyte Chlamydomonas reinhardtii, whereas no jacalin-related lectins could be retrieved from most other plant species. Legume lectin sequences account for the largest lectin families in Marchantia polymorpha, Azolla filiculoides, Salvinia cucullata, and Picea abies. Only one or two lectin motifs are identified in Cyanophora paradoxa (LysM), Micromonas sp. RCC299 , Chlorella NC64A  and Cyanidioschyzon merolae (LysM) while only malectins were retrieved from the genome of Porphyra umbilicalis. Clearly, there is no evidence for widespread or abundant lectin motifs in prasinophytes, glaucophytes, and rhodophytes.Plant lectin genes were exploited in key genomes of significant lineages in Archaeplastida. The comparative analysis of the lectin sequences retrieved from the rhodophytes families . RepreseArabidopsis thaliana, Glycine max, Cucumis sativus, and Oryza sativa). A comprehensive analysis of all the protein domains associated with plant lectin domains in the plant species under study  yielded an extensive list of protein domain arrangements , protein kinase or F-box domains are often found in combination with lectin domains in sisters of Streptophyta and vascular plants. It could be postulated that most of these domain architectures arose in a common ancestor of Streptophyta and/or chlorophytes, and that have been retained during evolution. However, there are a number of anomalies. The combination of an F-box domain with a Nictaba or LysM domain is shared by all Viridiplantae, while the F-box/jacalin combination is only present in higher plants -like domain are examples of protein domains that are not found in association with lectin domains in angiosperms . The EGFChlamydomonas reinhardtii that is involved in cell wall degradation. Next to Chlamydomonas reinhardtii, it was also reported in Volvox carteri  in reported . Furtherreported . In the Regarding the domain arrangement of lectin sequences in basal plant lineages, the multitude of sequences with tandem arrayed lectin domains is noteworthy. Sequences with a two or three LysM domains (in combination with a protein kinase domain) are conserved throughout Archaeplastida. In Arabidopsis and rice, they were identified as part of the plant immune system where they play key roles in the perception and recognition of danger signals. Similar proteins in legumes facilitate symbiotic communication . A sequeInvestigation of the expansion of the lectin families during the course of evolution can be linked to specific adaptive speciation events. Three plant lectin families that are present in both land plants and chlorophytes were selected for detailed analysis. To study the genomic evolution and expansion, the Nictaba, jacalin and hevein gene trees were reconciled with a species tree, including 29 plant genomes . The fulBrassica rapa-specific whole genome triplication event only contributes to a high number of duplications and losses in the jacalin family. A recent study showed that the Physcomitrella patens genome was subjected to two rounds of whole genome duplications. There is evidence that these events are common for mosses while they were not detected in the liverwort (Marchantia polymorpha) and hornwort lineages , gene losses were far more abundant (370) than duplication events (216). Whole genome duplication and triplication events have been added to the species tree in lineages . None ofa patens . OverallArabidopsis upon recognition of bacterial flagellin, the resilience of the plant immune system was explained by network buffering  whereas multi-copy genes are biased toward signaling, transport, metabolism and other cellular and biochemical functions or in other words, environmentally responsive genes . The extuffering . Interacuffering . Since suffering , and givArabidopsis thaliana, Oryza sativa, Glycine max and Cucumis sativus. Several cysteine and glycine residues are highly conserved in this motif known to be important for the structure and folding of the hevein domain  were identified. Most of the sequences contain all four motifs in a specific order . HoweverSeveral amino acids that were designated to be crucial for the carbohydrate-binding activity of Nictaba, jacalin and hevein lectins, are part of the identified conserved motifs of the lectin domains . Nevertheless, homologous plant lectins of one particular family can display different carbohydrate-binding specificities . Since nTo increase our understanding of the plant lectin families, we examined the origin of these protein families in the tree of life, with emphasis on the plant lineage. The widespread taxonomical distribution of some plant lectin domains was already described for the GNA, LysM, and ricin B lectin family, while the origin of the jacalin and Nictaba family was revisited. Taken together, our results suggest that different plant lectin families evolved in distinct ways. We documented variations of evolutionary paths at different levels, ranging from horizontal gene transfer, recombination of protein domains and discrepancy in gene loss and duplication events.The evolution of lectins is characterized by expansion of the different lectin families from algae to higher plants, alongside with the diversification of lectins in terms of domain architecture and possibly functionality. Homologs of most lectin families are also present in extant representatives of charophytes and chlorophytes. Unmistakably, the magnitude of the plant lectin family in rhodophytes, glaucophytes and prasinophytes is far less than that observed in tracheophytes. Only two groups of lectin motifs (LysM and ricin B) have been traced back to glaucophytes/rhodophytes. These are the most abundant plant lectin motifs in Bacteria, indicating that these plant lectin domains are most highly dispersed throughout the tree of life. Many of the essential plant features in land plants have their roots in charophyte algae . SeveralMost lectin sequences encode multi-domain proteins containing at least one lectin domain, suggesting that these proteins exert multiple biological activities. However, it remains challenging to predict the functionality of these lectins based on the domain sequences. Functional studies are needed to better understand their physiological roles. Although our knowledge of plant lectins has increased tremendously, a number of aspects on their evolutionary history remain incompletely understood. In the future, the availability of high quality chromosome-scale assemblies of more (plant) genomes will allow more detailed analyses , 2018. ISVH and EVD outlined and designed the study. SVH performed the research, analyzed the data, and prepared the manuscript. EVD conceived and supervised the study and critically revised the manuscript. All authors have read, revised, and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


IR2.1 potassium channels, producing inward rectifier potassium current (IK1), are important for final action potential repolarization and a stable resting membrane potential in excitable cells like cardiomyocytes. Abnormal KIR2.1 function, either decreased or increased, associates with diseases such as Andersen-Tawil syndrome, long and short QT syndromes. KIR2.1 ion channel protein trafficking and subcellular anchoring depends on intrinsic specific short amino acid sequences. We hypothesized that combining an evolutionary based sequence comparison and bioinformatics will identify new functional domains within the C-terminus of the KIR2.1 protein, which function could be determined by mutation analysis. We determined PEST domain signatures, rich in proline (P), glutamic acid (E), serine (S), and threonine (T), within KIR2.1 sequences using the “epestfind” webtool. WT and ΔPEST KIR2.1 channels were expressed in HEK293T and COS-7 cells. Patch-clamp electrophysiology measurements were performed in the inside-out mode on excised membrane patches and the whole cell mode using AxonPatch 200B amplifiers. KIR2.1 protein expression levels were determined by western blot analysis. Immunofluorescence microscopy was used to determine KIR2.1 subcellular localization. An evolutionary conserved PEST domain was identified in the C-terminus of the KIR2.1 channel protein displaying positive PEST scores in vertebrates ranging from fish to human. No similar PEST domain was detected in KIR2.2, KIR2.3, and KIR2.6 proteins. Deletion of the PEST domain in California kingsnake and human KIR2.1 proteins (ΔPEST), did not affect plasma membrane localization. Co-expression of WT and ΔPEST KIR2.1 proteins resulted in heterotetrameric channel formation. Deletion of the PEST domain did not increase protein stability in cycloheximide assays . WT and ΔPEST channels, either from human or snake, produced typical IK1, however, human ΔPEST channels displayed stronger intrinsic rectification. The current observations suggest that the PEST sequence of KIR2.1 is not associated with rapid protein degradation, and has a role in the rectification behavior of IK1 channels.K IR2.1 primary protein sequence, encoded by KCNJ2, have been attributed to biological function and molecular structure, but not all. KIR2.1 expression is found in a variety of excitable and non-excitable cells, like skeletal, smooth and cardiac muscle cells, neuronal cells, juxtaglomerular, and endothelial cells (IK1) is characterized by a larger inward than outward current from equal negative and positive deflections from the potassium equilibrium potential. This property allows for action potential formation in excitable cells, while providing a stable resting membrane potential in between action potentials  144-146], Endoplasmic Reticulum (ER) export , glutamic acid (E), aspartic acid (D), serine (S), and threonine (T) confined by two positively charged amino acids, lysine (K), arginine (R) or histidine (H). These domains were first identified in short living proteins and the PEST domain function was therefore deduced as protein instability domains . Indeed,equences  we notic1 using the standard settings.Protein sequences were individually loaded in the EMBOSS program ePESTfind toolHsKIR2.1ΔPEST was constructed by PCR amplification of a part of HsKCNJ2 (KCNJ2 open reading frame sequence with an in-frame deletion of the complete PEST sequence (KEEDDSENGVPE STSTDTPPDIDLH) and was cloned in pGEM-T-easy and subsequently subcloned into pcDNA4 (Life-Technologies). The similar procedure was followed for constructing California kingsnake LgKIR2.1ΔPEST using LgKCNJ2 (IR2.1 PEST sequence (KEEEDSDNGVPESTSTDTH).Human  HsKCNJ2  from pGE LgKCNJ2  and the 2. In time course experiments, cells for each time point were seeded on the same day, and drugs were added for the indicated time prior to harvest of all samples. For patch clamp electrophysiology, 3 days prior to measurements, HEK293T cells were grown on poly-L-lysine (Sigma-Aldrich) coated Ø 12 mm cover slips and transfected with human KIR2.1 (WT or ΔPEST) using Lipofectamine 2000  according to the manufacturer’s protocol. Recordings were performed 24 h after transfection. In western blot experiments, HEK293T cells were grown on 60 mm tissue culture dishes and transfected using linear PEI as described earlier (IR2.1 (WT or ΔPEST) using Lipofectamine according to the manufacturer’s protocol.HEK293T and COS-7 cells were cultured in Dulbecco’s Modified Eagles Medium  supplemented with 10% fetal calf serum , 2 mM L-glutamine (Lonza), and 50 U/mL penicillin and 50 mg/mL streptomycin (both Lonza) at 37°C with 5% CO earlier . In immuChloroquine  was dissolved in sterile water at a concentration of 10 mM and stored at −20°C. Cycloheximide  was dissolved in ethanol at a concentration of 5 mg/mL, stored and aliquoted at −20°C until use. SPM was prepared in DEPC water at a concentration of 50 mM. All drugs were diluted on the day used.IR2.1 , Pan-Cadherin . Cell nuclei were stained with 4′,6-diamidino-2-phenylindole  during secondary antibody incubation. Secondary antibodies used were donkey anti-mouse DyLight  or donkey anti-goat Alexa Red . Conventional fluorescence microscopy was performed on a Nikon eclipse 80i light microscope equipped with a 40× objective (NA 0.75). Confocal images were obtained using a Zeiss Axiovert 200 M confocal microscope  equipped with a 63× water immersion objective (NA 1.2) plus 29 digital zoom. Excitation was performed with an air-cooled Argon ion laser  for GFP and a HeNE  laser for DyLight.COS-7 cells were stained essentially as described earlier . AntibodIR2.1 antibody used was identical as used for immunofluorescence microscopy. Equal protein loading was determined by Ponceau staining.Cell lysis, western blot and subsequent analysis was performed as described earlier . KIR2.1 IR2.1 expression constructs together with a GFP expression construct to identify transfected cells. Inside-out patch clamp measurements on excised membrane patches were performed using an AxoPatch 200B amplifier controlled by pClamp9 software  at 21°C as described before : 125 KCl, 4 EDTA, 2.8 KH2PO4, 7.2 K2HPO4 (pH 7.2 with KOH), and pipette solution contained (mM): 145 KCl, 5 HEPES, 1 CaCl2 (pH 7.4 with KOH). Excised patches were placed in close proximity of the inflow region of the perfusion chamber. Measurements were started following washout of polyamines/Mg2+ from the channel pore, observed by the disappearance of current rectification.HEK293T cells were transfected with WT or ΔPEST Kd before . To recoKIR2.1 measurements were performed by applying 1 s test pulses ranging between -120 and +30 mV, in 10 mV increments, from a holding potential of -40 mV, and with series resistance compensation of at least 70%. Signals were low-pass filtered at 2 kHz and sampled at 4 kHz. Liquid junction potential (LJP) was determined with the built in “Junction Potential Calculator” application of pCLAMP. Using the current solutions, LJP was 14.7 mV. Steady state current at the end of the pulse was normalized to cell capacitance and plotted versus test potential (corrected for LJP).Whole cell patch clamp measurements were done as described before  using ant-test or two-way ANOVA followed by a post hoc Bonferroni test. Results with P < 0.05 were considered as statistically significant. Statistically analyses were performed using Prism 6 .Group averages are presented as mean ± SEM, unless indicated otherwise. Differences between groups were tested by (un)paired Student’s IR2.1 amino acid sequences covering the phyla from fish to man (IR2.1 sequences of the lobe finned fish Coelacanth (XP_005992210) and of the primitive cartilaginous fish elephant shark (XP_007886827) whose sequences also contained PEST domains with a high PEST score   with a PEST score of 9.39 that starts upstream from the KIR2.1 PEST domain  . In contT domain .IR2.1 protein lacking the complete PEST domain (ΔPEST) was constructed to gain insight into the biological role of the PEST domain. Upon transfection in HEK293T cells, ΔPEST channel protein was detected on Western blot using an antibody against the N-terminus having, as expected, a lower apparent Mw as compared to WT channel proteins   . Thus, rP = 0.31) for WT and ΔPEST, respectively)  .IR2.1 channels were performed in the absence of polyamines and Mg2+ using a ramp protocol from −100 to +100 mV   The strongest decrease in current was observed upon perfusion with 0.1 μM spermine .To better assess inward rectification properties, inside-out measurements of WT and ΔPEST K +100 mV . Under b +100 mV . Quantifan ± SD) . Upon apan ± SD) . Finallyan ± SD)   .Both WT and ΔPEST channels from snake produced typical Kysiology . When usan ± SD) . Distriban ± SD) . As for an ± SD)  . Deletion of the PEST domain did not increase T½ which is in contrast to the original PEST domain hypothesis as mentioned above. From these results we conclude that the PEST domain in KIR2.1 proteins does not promote protein instability and is not responsible for rapid protein degradation.PEST domains are defined by a specific signature, i.e., a stretch of amino acids rich in P, E, D, S and T most often confined by positively charged residues on both sides, rather than by a determined sequence motif. This may explain why this domain has not been recognized in the K present . However present . Upon ecIR2.1 PEST domain (residues 385–409) is located between the ER export signal FCYENE (374–379) and the PDZ binding domain ESEI (425–427). Similarly, the snake KIR2.1 PEST (383–401) is located between ER export signal (372–377) and PDZ binding domain (422–425). In crystallization studies, the last 57 residues of the mouse KIR2.1 channels were found to lack intrinsic structural rigidity, and it was suggested that this domain might require interactions with other regions of the protein and/or cytoplasmic proteins to adopt one or more defined conformations .Inward rectification in K reached . As rectIR2.1 channels awaits further work, in which in vivo models with ubiquitous expression of ΔPEST channels may provide first clues into which of the many cell types that express KIR2.1 channel proteins, the PEST domain plays a prominent role. Only then can clinical implications be envisioned.A potential physiological role for the PEST domain in KThe datasets generated for this study are available on request to the corresponding author.MQ, YJ, MH, MV, FR, BK, and MvdH performed the research. MQ, YJ, MH, MV, FR, and MvdH analyzed the results. MvdH designed the study. MQ and MvdH wrote the manuscript. All authors reviewed the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The atypical cyclin-dependent kinase 5 (CDK5) is considered as a neuron-specific kinase that plays important roles in many cellular functions including cell motility and survival. The activation of CDK5 is dependent on interaction with its activator p35, p39, or p25. These activators share a CDK5-binding domain and form a tertiary structure similar to that of cyclins. Upon activation, CDK5/p35 complexes localize primarily in the plasma membrane, cytosol, and perinuclear region. Although other CDKs are activated by cyclins, binding of cyclin D and E showed no effect on CDK5 activation. However, it has been shown that CDK5 can be activated by cyclin I, which results in anti-apoptotic functions due to the increased expression of Bcl-2 family proteins. Treatment with the CDK5 inhibitor roscovitine sensitizes cells to heat-induced apoptosis and its phosphorylation, which results in prevention of the apoptotic protein functions. Here, we highlight the regulatory mechanisms of CDK5 and its roles in cellular processes such as gene regulation, cell survival, and apoptosis. The proline-directed serine/threonine cyclin-dependent kinase 5 (CDK5) is an atypical member of the well-studied family of cyclin-dependent kinases (CDKs) . CDK5 waLew et al. reported the same kinase as brain proline-directed protein kinase due to its functional similarity to cdc2 in the bovine brain . In 1993−/− mice, however seizures are reduced upon p39 activation in p39−/− mice with no detectable abnormalities.Unlike other CDKs that require the binding of cyclins in order for their activation, CDK5 requires the binding of p35, p39, or p25 (a proteolytic fragment of p35) for activation. p35  was first discovered due to its association and activation of CDK5 ,18,19. H−/− mice [−/− mice show no detectable abnormalities [−/− double-knockout mice show a more severely affected phenotype, as compared with p35−/− mice, which is identical to CDK5−/− mice [−/− mice, p35 and p39 are thought to be necessary and sufficient for both normal CDK5 activity and proper neurodevelopment [Interestingly, the subcellular localization of CDK5 is dependent on the activator to which it is bound. Specifically, CDK5 remains primarily cytosolic when it is not bound to any activators, whereas interaction with either p35 or p39 results in localization of CDK5, primarily to the plasma membrane and perinuclear region, due to myristoylation of p35 and p39, though CDK5/p35 complexes can also be seen in the cytosol . As show−/− mice ,32. On tmalities . However−/− mice . Due to elopment ,12,33. Selopment ,35,36 Laelopment . Bindingelopment ,38.The kinase activity of CDK5 is primarily regulated by the presence, amount, and balance among available p25, p35, and p39 , p35 and−/− mice reduce p35/p25 protein levels and CDK5 activity in brain tissues [−/− mice during cortical development [Treatment of PC12 cells (rat pheochromocytoma) with nerve growth factor (NGF) results in the strong induction of p35 expression that is ERK-dependent and mediated by early growth response protein 1 (Egr1) . In supp tissues . Chang eelopment ; p35 andelopment . In the elopment .Protein levels of p35 and p39 are also regulated by protein degradation. Studies have shown that p35 has a half-life of ~30 min and is ubiquitinated in COS-7 cells (monkey kidney fibroblast), mouse primary cortical neurons, intracerebral hemorrhage (ICH) models of rats, and primary cortical neurons ,48,49. FIn addition to levels of p25/p35/p39 protein, CDK5 activity is also regulated by direct phosphorylation of CDK5, though the effect of CDK5 phosphorylation on CDK5 activity is dramatically different from that of other CDKs. Commonly, CDK activity is inhibited by phosphorylation of both Thr14 and Tyr15 by the dual specific kinases Wee1 and myelin transcription factor 1, while phosphorylation of CDK1/2 on residue Thr160/161 by CDK-activating kinase (CAK) is required for activation of CDK1/2 activity ,36,53. CCDK5 activity can also be inhibited by various pharmacological compounds. The earliest, and currently the most popular, inhibitors of CDK5 are the purine-based compounds olomoucine and roscovitine ,62,63. T−/− and p35/p39−/− mice have revealed that these mice die during the perinatal period of development due to widespread disruption of neuronal migration in the cerebral cortex, hippocampus, and cerebellum, resulting in a lack of cortical laminar structure and cerebellar foliation [−/− mice [−/− mice as compared with wild-type mice [−/− mice, p35−/− mice have severe defects in cortical lamination, due to lack of CDK5/p35 kinase activity and improper neuronal migration, and suffer from seizures and sporadic adult lethality [−/− and p35−/− mice do share similar phenotypic abnormalities, it should be noted that these two phenotypes are not identical as p39 can maintain limited function of CDK5 in p35−/− mice [CDK5 is an essential player in central nervous system development, function, and disease. Its function is indispensable for proper neuronal migration and differentiation, axonal elongation, and synaptic function. Also, association of CDK5 with p25 leads to altered regulation of CDK5 that promotes neuronal apoptosis and development of neurological diseases such as Alzheimer’s and Parkinson’s disease ,53,68,69oliation ,71. The −/− mice . Studiesype mice . In addiethality . Though −/− mice ,32.CDK5 has also been demonstrated to be involved in axonal elongation. Studies have demonstrated that there exists a high degree of temporal correlation among CDK5 activation, p35 expression, and formation of axonal tracts in the developing brain ,68,75. CThe proteolytic p25 fragment of p35 exhibits a different subcellular localization with and is more stable that its precursor p35. CDK5/p25 have shown to phosphorylate both Tau and MAP1B found in neurofibrillary tangles (NFTs) compared with CDK5/p35 ,31. CDK52+-induced insulin exocytosis in pancreatic β cells [CDK5 has also been identified to play important roles in processes such as cell death and proliferation, angiogenesis, migration of epithelial and cancer cells, inflammation, myogenesis, glucose metabolism, and insulin secretion in non-neuronal cells ,90,91,92 β cells .The function of CDK5 has also been studied in cells of hematopoietic lineage and has been implicated in processes such as response to inflammation, proliferation, and apoptosis ,95. OverAs future research, more studies should be done on the role of CDK5 in protein regulation, as a study has shown that pro-apoptotic BH3-only protein Noxa is required for hyperthermia-induced Mcl-1 degradation and apoptosis . Also, iAutophagy is an essential natural regulating mechanism that governs the removal of unnecessary and long-lived cellular components. In healthy mammalian cells, the dominant activity is directed towards intracellular homeostatic turnover of proteins, mediating self-renewal energy generation, metabolism, and cell death ,105,106.Regulation of apoptosis is critical for cell survival during stress and for proper removal of aged and damaged cells. Deregulation of apoptosis has been found to be essential for many diseases, including cancer and many neurodegenerative diseases. Post-translational modifications, such as CKD5 phosphorylation, have been shown to regulate the function of various regulatory proteins, including members of the Bcl-2 family of pro- and anti-apoptotic proteins. Hyperthermia is one type of stress that is able to induce apoptosis through activation of the intrinsic pathway and results in changes in phosphorylation and activity of members of the Bcl-2 family. This review highlighted the regulatory mechanisms of CDK5 and its roles in cellular processes such as gene regulation, cell survival, and apoptosis. However, we seek to highlight the mechanisms of this atypical cyclin member phosphorylation that may aid in the hunt for additional targets with potential therapeutic relevance.


The modular structural domains of multidomain RNA enzymes can often be dissected into separate domain RNAs and their noncovalent assembly can often reconstitute active enzymes. These properties are important to understand their basic characteristics and are useful for their application to RNA-based nanostructures. Bimolecular forms of bacterial RNase P ribozymes consisting of S-domain and C-domain RNAs are attractive as platforms for catalytic RNA nanostructures, but their S-domain/C-domain assembly was not optimized for this purpose. Through analysis and engineering of bimolecular forms of the two bacterial RNase P ribozymes, we constructed a chimeric ribozyme with improved catalytic ability and S-domain/C-domain assembly and developed a pair of bimolecular RNase P ribozymes the assembly of which was considerably orthogonal to each other. In the molecular evolution of protein enzymes, the emergence of more complex structures through gene fusion and less complex structures through gene fission are important events in the expansion of the diversity of protein structures and functions ,2. Gene In natural evolution as well as artificial engineering of functional RNAs with three-dimensional (3D) structures, fusion or fission of the RNA strands must generate multidomain RNAs or smaller structural RNAs, respectively. Smaller structural RNAs can also reconstitute the parent multidomain structures and their functions through noncovalent assembly ,13,14,15Escherichia coli and Bacillus subtilis ribozymes ..E. coli ucidated . TherefoT. thermophilus sys1 bimolecular ribozyme with that of the E. coli sys1 ribozyme  pairs of S-domain and C-domain RNAs (Ec-Sd/Tth-Cd and Tth-Cd/Ec-Sd chimeric ribozymes). Among the four sys1 bimolecular ribozymes, the E. coli ribozyme was poorly active and the Ec-Sd/Tth-Cd chimeric ribozyme showed no activity  makes a positive contribution to the catalytic activity of sys1 bimolecular ribozymes. We then performed an EMSA to examine whether the S-domain RNA and the C-domain RNA, each of which showed folding uniformity to yield a single band  and the Tth-Sd/Ec-Cd ribozyme (lanes 11 and 12) exhibited no stable S-domain/C-domain complexes, suggesting that the two active bimolecular sys1 ribozymes were structurally unstable  and T. thermophilus sys2 ribozyme (lanes 9 and 10) formed complexes between their S-domain and C-domain based on mobility shift of their S-domain RNA in the presence of the C-domain RNA (E. coli and Ec-Sd/Tth-Cd ribozymes) showed no mobility shift in S-domain RNA (lanes 5 and 7), suggesting no stable complex formation  receptor motif. The R(11nt) receptor motif specifically and strongly recognizes a GAAA loop . In the E. coli sys1 bimolecular ribozyme, the variant bearing the GAAA–R(11nt) pair cleaved 58% of the substrate pre-tRNA in the initial burst phase  pair also significantly improved the activities of the remaining three sys1 ribozymes . In the st phase B althougst phase B. The L9st phase C. Modulast phase  20,21].,21.E. coIn EMSA, complex formation of S-domain/C-domain bearing GAAA/R(11nt) pair was confirmed by the mobility shift of the labeled RNA component in the presence of the partner RNA , whereas mismatched P6 base pairs significantly reduced the activity. Therefore, we introduced the P6m1 base pairs into the Tth-Sd/Ec-Cd sys2 ribozyme  and ebRz-β (0.098 min−1), respectively  to determine whether its bimolecular format is promising as a platform for the development of supramolecular ribozyme polymers. Comparative analysis of the bimolecular T. thermophilus and E. coli ribozymes indicated that a chimeric bimolecular ribozyme consisting of the T. thermophilus S-domain RNA and E. coli C-domain (Tth-Sd/Ec-Cd sys2 ribozyme) had promising properties related to catalytic ability and complex formation. In EMSA analysis, no S-domain/C-domain complex of the E. coli sys2 ribozyme was observed (E. coli sys2 ribozyme may be induced by the association with pre-tRNA. The complex was detected in the T. thermophilus sys2 ribozyme (T. thermophilus sys2 ribozyme was less efficient than that of the E. coli sys2 especially under conditions of substrate excess (E. coli ribozyme at 50–60 °C but they were often less active than the E. coli ribozyme at 30–40 °C. The relatively poor activities of thermophilic RNase P ribozymes at 30–40 °C are partially due to slow product release [This study was performed to investigate A-type bacterial RNase P ribozyme from a thermophilic bacterium (observed . This obe excess B. These T. thermophilus ribozyme formed a stable S-domain/C-domain complex, while the E. coli ribozyme was distinctly more active at 37 °C. This was largely resolved in the chimeric Tth-Sd/Ec-Cd sys2 ribozyme because it formed a stable complex and exhibited promising catalytic activity. Although we did not exploit the molecular mechanism of action of the Tth-Sd/Ec-Cd sys2 ribozyme to exhibit promising structural and catalytic properties, these properties may be due to the T. thermophilus S-domain, which is rigid at 37 °C, and the E. coli C-domain, which must adapt its catalytic ability at 37 °C. Further improvement of the bimolecular Tth-Sd/Ec-Cd sys2 ribozyme was achieved by optimizing the interdomain tetraloop/receptor interaction between L9 in the S-domain and P1 in the C-domain. Modulation of tetraloop/receptor interactions has been employed successfully to redesign the structural and catalytic properties of group I intron ribozymes [The ibozymes . This stibozymes . This stInstallation of orthogonality to the RNA–RNA interface between the S-domain and C-domain relied mainly on the substitution of base pairs in the P6 element and was also assisted by the two sets of tetraloop/receptor interactions . The resT. thermophilus S-domain RNA and E. coli C-domain showed better properties with regard to assembly and catalysis than homologous S-domain/C-domain combinations. The assembly and catalytic properties of the chimeric ribozyme were improved by installation of the evolved form of GNRA/receptor interaction. Based on these modifications, a pair of orthogonal bimolecular RNase P ribozyme derivatives was developed. Although problems remain to be resolved, these derivatives would serve as advanced forms of RNase P ribozyme for the construction of catalytic RNA nanostructures. The strategies described in this study will be applicable to the engineering of other functional RNAs to elucidate their structure–function relationships and also for their application as RNA nanobiotechnology tools.A heterologous S-domain/C-domain combination consisting of


Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains.This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark.Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches.https://bitbucket.org/sonnhammergroup/domainoid/ Genes descended from the same ancestral sequence, diverging from each other through speciation, are usually referred to as orthologs . These aMost orthology inference methods, such as OMA , EggNOG To apply a domain-aware approach for orthology inference one can either use an unsupervised algorithm for domain detection  or emploAs examples of such previous work, domain-based orthology detection is used by the microbial genome database MBGD  which utWe here present a novel domain-aware approach, based on letting the InParanoid  algorithEscherichia coli, containing 4313 sequences and Homo sapiens, containing 21,008 sequences, this first step resulted in a total of 85,551 domain or domain-equivalent sequences. Out of these, 271 protein sequences from Escherichia coli and 1932 from Homo sapiens had no domain assignments, hence these were fully included as potential single (orphan) domain sequences. Interdomain regions longer than 30 aa that were not assigned with any domain by Pfam, were included as domains labeled as unknown, together with a consecutive number, eg “UNK1”. For Escherichia coli 3271 and for Homo sapiens 32,783 such domains were included. Domain sequences classified by Pfam as repeats were excluded, 148 for Escherichia coli and 4413 for Homo sapiens. Domains overlapping with more than half of its length were excluded, 47 for Escherichia coli and 112 for Homo sapiens. The resulting dataset included 9461 domain or domain-equivalent sequences for Escherichia coli and 76,090 sequences for Homo sapiens. Running InParanoid on the domain sequences resulted in 2272 orthologous domains, generated from 894 ortholog groups.In the first step of running Domainoid, domain sequences are extracted from the proteomes using Pfam. For our selected proteomes, Homo sapiens and Escherichia coli, Domainoid found 2126 orthologous proteins based on the predicted orthologs of which 1671 had exactly one orthologous domain, while the remaining 455 proteins had multiple orthologous domains. To give a conservative estimate of how many of these may represent cases of discordant domain orthology, we defined primary protein sequences among the proteins with multiple orthologous domains, and secondary proteins as sequences containing domains orthologous to one or more domains in the primary protein. If a primary protein had secondary proteins with different subsets of orthologous domains to the primary protein, this would indicate discordant domain orthology. We found 92 such primary proteins between Homo sapiens and Escherichia coli, which represent cases of different evolutionary histories for different domains on the same protein. For a complete listing of the discordant domain orthologs identified, see Additional file In order to assess the usefulness of orthologous domains generated when running InParanoid on the domain equivalent sequences, we looked for cases where the domain-based approach for orthology inference resulted in orthologous pairs not found by the full-length approach. To identify cases where discordant domain orthologies, i.e. orthologous pairs where gene fission/fusion or domain shuffling may have taken place, the resulting set of ortholog pairs from Domainoid were inspected. For the two species Homo sapiens with four domains, Pfam domains PRK (Phosphoribulokinase/Uridine kinase) and UPRTase (Uracil phosphoribosyltransferase), and two interdomain, unannotated regions labeled UNK1 and UNK2, have one orthologous domain on each of the Escherichia coli proteins P0A8F4, Uridine kinase, and P0A8F0, Uracil phosphoribosyltransferase. The sequence for protein P0A8F4 almost entirely consists of the domain PRK, and protein P0A8F0 almost entirely of the domain URPTase. The Homo sapiens protein Q9NWZ5 is involved in catalyzation of UPM biosynthesis in the salvage pathway, similar to the Escherichia coli proteins identified as domain orthologs. The orthologous domains, PRK and UPRTase have been shown to appear in different constellations in different species, either in separate proteins or in one protein chain. It has previously been shown that the appearance of these domains in separate proteins, as in Escherichia coli implies a functional dependency between the proteins, where the absence of one of them resulted in growth inhibition [Escherichia coli proteins have been merged with interdomain regions into Homo sapiens protein Q9NWZ5. The orthology of these domains is supported by the Neighbor-joining trees found in Additional file Out of the discordant domain orthologs, 261 protein pairs could be generated, and from these, 170 protein pairs could not be identified by the full-length approach inParanoid when run using default settings. An example of such a case is shown in Fig. hibition . This diThe inability of InParanoid to recognize these discordant domain orthologs can to some extent be explained by the length filter, by default dismissing orthologous proteins that have a matching sequence shorter than half of the length of the longest sequence. Running InParanoid with sequence overlap cutoff of 0 and a segment coverage cutoff of 0 does detect one of the pairs, Q9NWZ5/P0A8F4, but the other pair remains undetected.Escherichia coli, bifunctional NAD(P)H-hydrate repair enzyme Nnr, having four secondary proteins, A6XGL0, YjeF N-terminal domain-containing protein 3, Q8IW45, ATP-dependent (S)-NAD(P)H-hydrate dehydratase, Q8NCW5, NAD(P)H-hydrate epimerase, and E7ENQ6, an uncharacterized protein from Homo sapiens. The domain architectures of these proteins are shown in Fig. Homo sapiens proteins, A6XGL0, Q8NCW5, and E7ENQ6 all have the orthologous domain YjeF_N (YjeF-related protein N-terminus), while the fourth, Q8IW45, has one unique domain, orthologous to the second annotated domain in the primary protein, Carb_kinase (Carbohydrate kinase). The Escherichia coli protein, P31806, has two functions, epimerization of NAD(P) HX, which is shared by the proteins orthologous to domain YjeF_N, and dehydration of NAD(P) HX, shared by the protein orthologous to the Carb_kinase domain, indicating different evolutionary histories for the domains. None of these ortholog pairs are identified by OMA, Hieranoid or InParanoid with default settings. Running InParanoid with a sequence overlap cutoff of 0 and a segment coverage cutoff of 0 identifies only one of the four pairs, P31806/Q8IW45. The orthology of these domains is supported by the Neighbor-joining trees in Additional file Among the discordant domain orthologs generated, 51 out of 92 proteins defined as primary had more than two secondary proteins. Among these cases, many display a behaviour where two or more of the secondary proteins are very similar in its domain architecture, and contain the same orthologous domains to the primary protein, while other secondary proteins contain different orthologous domains to the primary protein. One example of this is P31806 in Domainoid can be used to call full-length protein orthology if more domains than a preselected threshold are orthologous. As InParanoid inferences have been shown to be reliable in benchmarks , we usedIn order to pick an alpha threshold, we ran Domainoid with an alpha threshold at eleven different equally spaced intervals see Fig. . For theOn the level of full-length sequence ortholog pairs, there are three main scenarios. InParanoid and Domainoid may both identify the relationship, or it may be found by only one or the other of the methods. InParanoid full-length analysis of the two tested proteomes yielded 1222 ortholog pairs, whereas Domainoid at alpha threshold 0.3 yielded 1259 domain ortholog pairs. We note that InParanoid identified 255 ortholog pairs that could not be found by Domainoid at any threshold. This loss in sensitivity is likely due to the increased difficulty to detect orthology for shorter sequences, as well as the fact that there is an information loss, where similarity on the full-length sequence might be missed when the sequence is split into smaller pieces. Four hundred seven of the domain ortholog pairs were identified by Domainoid only. By mapping these onto ortholog groups resulting from conventional InParanoid analysis we can distinguish 9 conflicting pairs, where both proteins were assigned by InParanoid but in conflicting ortholog groups, 154 domain ortholog pairs with one protein not assigned to an ortholog group in the InParanoid results, and 244 domain ortholog pairs where neither protein was assigned to an ortholog group by InParanoid. This distribution of Domainoid and InParanoid ortholog pairs is shown in Fig. To further assess under what conditions a domain-based approach works better than full-length orthology inference with InParanoid, we inspected Domainoid-only protein-level ortholog pairs with one or two proteins missing from conventional InParanoid results when using an alpha threshold of 0.3. Out of 398 such ortholog pairs on the protein level, 374 (~ 94%) had only one orthologous domain.Homo sapiens protein DnaJ homolog subfamily B member 9, and Escherichia coli protein Chaperone protein DnaJ, see Fig. Homo sapiens/Escherichia coli dataset. The pair could also not be identified as an ortholog pair in any of the databases OMA or Hieranoid. A Neighbor-joining tree confirming the domains as closest pairs can be found in Additional file Among these single domain pairs, we find many cases similar to the pair Q9UBS3/P08622, Homo sapiens protein P22102, Trifunctional purine biosynthetic protein adenosine-3 and Escherichia coli protein P08178, Phosphoribosylformylglycinamidine cyclo-ligase, see Fig. Escherichia coli protein P08178 these three domains covers almost the entire sequence, but for the Homo sapiens protein P22102, these three domains are surrounded by other named domains as well as interdomain regions. This ortholog pair is not found by OMA, Hieranoid, or InParanoid at any sequence overlap cutoff and segment coverage cutoff. A Neighbor-joining tree supports the AIRS domains as orthologous, see Additional file Homo sapiens/Escherichia coli dataset with an alpha threshold of 0.3. None of these proteins are identified in any ortholog pair by InParanoid, most likely because the similar regions are scattered over the full protein sequence, making it difficult to detect sequence similarity.One of the cases where Domainoid identifies ortholog pairs with more than one common domains, is for Homo sapiens/Escherichia coli dataset, where InParanoid identifies a higher percentage of orthologs not detected by Domainoid. For such cases, the orthologs inferred by InParanoid could be enriched with non-conflicting new orthologs inferred only by Domainoid, to ensure as little loss of information as possible. To get an estimation of the quality of the orthologs inferred using Domainoid to enrich InParanoid orthologs, a benchmark was also performed on the merged set of orthologs for the fungal dataset, and for this merged set of data, a Domainoid alpha threshold of 0.4 was shown to generate the best results  and filters assuring that all matching segments cover at least 50% of the longer sequence. The best matching pairs of sequences from two species define seed orthologs. Using higher bitscores as a proxy for lower evolutionary distances, additional inparalogs are recruited around the seed ortholog pairs if their bitscore with the seed ortholog in the same species does not fall below the bitscore of the seed pair. Sets of seed orthologs and inparalogs define ortholog groups, within which all pairs of proteins that belong to different species are orthologs. When conventional InParanoid is run on full-length sequences, proteins from different species in the same ortholog groups are considered to be ortholog pairs and those from the same species as in-paralogs (co-orthologs relative to the group members in the other species) .Domainoid differs from conventional InParanoid in the first and last steps of this procedure. Instead of starting with all full-length sequences, most of the sequences are replaced with sets of region cuts corresponding to identified domains. A standard InParanoid is then run with these sequences as input, resulting in ortholog groups containing single domains rather than full-length sequences. These ortholog groups can then either be analyzed on the domain level or be used in aggregation to infer whole-protein ortholog pairs based on how many of their domains are orthologous. A general overview of steps in the Domainoid algorithm is shown in Fig. For a set of input proteomes, the first step of Domainoid analysis is to identify instances of protein domain families in the sequences. This is done using the PfamScan tool. Additionally, any regions longer than 30 residues that are not matched to a known Pfam domain family are included as potential novel or orphan domain sequences, or potentially remotely diverged domain sequences. These are included in the same way as proper domain hits are in further analysis, whereas shorter unassigned regions are considered more likely to simply be linker regions or terminals and are therefore discarded. Any full-length genes without hits to known domains are similarly included in its complete length as potentially novel domain sequences. Domains identified by Pfam as Repeats are excluded from the set of sequences, and domains that are overlapping with more than half of its length are similarly excluded from the complete set. In cases where two domains are overlapping with more than half of its length, the longest sequence is kept. The resulting joint set of known and potentially novel domain sequences in each of the two species are then analyzed as per the conventional InParanoid pipeline, and Domainoid analysis then proceeds by merging and analyzing the resulting orthology groups pairwise . The results can then either be analyzed as ortholog pairs on the domain level, or be projected on a protein-level as domain orthologs.The orthologous domains generated by Domainoid can be used to identify discordant domain orthology, i.e. proteins with domains that are orthologous to different proteins. Such domains have distinct evolutionary histories, resulting from gene fission/fusion or domain shuffling. To identify potential discordant orthologs, we define primary protein sequences as having orthologous domains to more than one other protein, and secondary proteins as sequences in the other species containing domains orthologous to a subset of the domains in the primary protein. If a primary protein has at least two secondary proteins with mutually exclusive orthologous domains to the primary protein, they are considered to be potential discordant orthologs.As in a conventional InParanoid analysis, Domainoid’s orthology groups are identified, each thus derived from a single domain-length sequence in the last common ancestral species of the two species analyzed in each case. If a set of proteins have the same domain architectures and the Domainoid ortholog groups corresponding to each of these domains support the same orthology relationship, then it is straightforward to conclude that this relationship also holds for the full-length sequences, as supported by the integrated results of the domain-level analysis.In scenarios where orthology relationships hold for individual domains within a set of proteins, but not for all domains, it is necessary to decide whether full-length sequence proteins are orthologs. This is achieved by defining an alpha threshold parameter. For each pair of potential orthologs (proteins sharing at least one domain), the alpha parameter is calculated by counting the number of domains belonging to the same ortholog group, as assigned by InParanoid, divided by the number of domains these two proteins have in total. If alpha value is at least as large as a predefined threshold then a protein pair is considered orthologous. The calculation is more intuitively depicted in Fig. When using Domainoid to recover orthologs on the protein level, there is a risk of missing orthology relationships detectable only in full protein sequences but not with individual domains. In order to compensate for this, Domainoid can be used to complement a set of orthologs generated by conventional InParanoid. To perform this merger, Domainoid and InParanoid are run on the same data, and all orthologs detected by InParanoid are added to the merged set together with the orthologs that are uniquely identified by Domainoid. In cases where orthology assignments are conflicting, i.e. where both proteins are assigned by both methods but in conflicting ortholog groups, only the InParanoid pair is kept, since the orthologs predicted by InParanoid have previously proven to be reliable in benchmarks .Escherichia coli and Homo sapiens meet these criteria, and were selected for analysis of Domainoid results. The resulting orthologs generated by Domainoid on this dataset were compared to orthologs inferred by InParanoid [To assess the validity of Domainoid inferences and for benchmarking our results, we used the curated set of reference proteomes selected within the Quest for Orthologs initiative (QfO v2018–04) . For allParanoid  for the Batrachochytrium dendrobatidis, Candida albicans, Neosartorya fumigata, Neurospora crassa, Phaeosphaeria nodorum, Puccinia graminis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Sclerotinia sclerotiorum, Ustilago maydis, Yarrowia lipolytica, and Cryptococcus neoformans. The resulting orthologs between these fungal species were uploaded to the Orthology benchmarking web service [To perform the benchmark we used a subset of the Quest for Orthologs dataset, the fungal species  service  which coTo evaluate pairs of domain orthologs in the examples, we used BLAST 2.2.18  to identAdditional file 1: Figures S1–S6. containing trees to support the orthology for the examples, Figure S7. showing the distribution of orthologs from Domainoid in relation to InParanoid for fungi, and Figure S8. showing performance of Domainoid merged with InParanoid in the Generalized species tree discordance test for fungi on different alpha thresholds.Additional file 2. Including a list of discordant domain orthologs for Homo sapiens/Escherichia coli.