Video delivered over IP networks in real-time applications, which utilize RTP protocol over unreliable UDP such as videotelephony or live-streaming, is often prone to degradation caused by multiple sources. The most significant is the combined effect of video compression and its transmission over the communication channel. This paper analyzes the adverse impact of packet loss on video quality encoded with various combinations of compression parameters and resolutions. For the purposes of the research, a dataset containing 11,200 full HD and ultra HD video sequences encoded to H.264 and H.265 formats at five bit rates was compiled with a simulated packet loss rate (PLR) ranging from 0 to 1%. Objective assessment was conducted by using peak signal to noise ratio (PSNR) and Structural Similarity Index (SSIM) metrics, whereas the well-known absolute category rating (ACR) was used for subjective evaluation. Analysis of the results confirmed the presumption that video quality decreases along with the rise of packet loss rate, regardless of compression parameters. The experiments further led to a finding that the quality of sequences affected by PLR declines with increasing bit rate. Additionally, the paper includes recommendations of compression parameters for use under various network conditions. A high standard of living, education, and more opportunities, along with people’s demands for such better conditions, has been constantly increasing over the last decades. Naturally, this applies to expectations in all areas of life, including entertainment and technology. Much like the rest of the world, Internet service providers, as well as broadcasting companies, want to bring their customers the best possible experiences. This individual user impression, also referred to as quality of experience (QoE) is highly dependent on quality of service (QoS) parameters. In the field of video transmission, these further depend on factors such as latency, jitter, or packet loss rate (PLR). However, although such factors are easily measurable, QoE cannot be quantified so effortlessly. Nowadays, one of the most popular network services is live video streaming, which is growing on a huge scale ,2. HowevThis paper is focused primarily on evaluating the influence of PLR on the quality of H.264/AVC and H.265/HEVC-encoded full HD and ultra HD video sequences. The different combinations of the resolution and compression parameters were used. Objective and subjective evaluation methods, namely peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM), and absolute category rating (ACR) were employed for video-quality quantification. Additionally, the principle of the subjective ACR method enabled further research into the combined effect of PLR and compression parameters on perceived video quality. As a result, this paper also suggests the most suitable combination of resolution, bit rate, and codec for use under different conditions.The paper is organized as follows. There are several research papers that deal with QoS and QoE evaluation, especially the performance assessment of various compression standards or the effect which has the transmission over noisy communication channel on the video quality. Coding structures, syntax, various tools, and settings relevant to coding effectivity were described in that paper. Human perception of compression, spatial and temporal information was examined in . The autA parametric planning model combining characteristics of the channel and the video is introduced in . The vidThe authors of  claimed In  a methodThe purpose of this paper is not to point out the difference between QoS and QoE. These concepts, their correlation, and the derived mapping function were described in our previous paper . The difThe basic requirements for reference sequences intended for further processing are uncompressed format, high bit depth, resolution and frame rate, suitable aspect ratio, and sufficient diversity in terms of scene content. Meeting all these standards, eight high-quality video sequences were selected from the Shanghai Jiao Tang University dataset . Common n filtered by using the Sobel filter, n and Spatial perceptual information (SI) indicates the amount of detail in the video frames. The equation for calculating SI, based on the Sobel filter, is defined asBoth SI and TI are calculated for the luminance component of the frames only. Higher TI indicates more motion in the scene, whereas higher SI is generated by frames with more edges and disparity in luminance . PreviewThe Bund Nightscape is a time-lapse video sequence capturing cars driving through a night city near a river. The video was shot from a high angle with a static camera. The only sources of movement are passing cars, people in the streets, and flags hoisted on the roofs of buildings. The Campfire Party is a nighttime video sequence, picturing a group of people posing for a photograph by a campfire. The camera is almost still, except for the slight zoom in the end of the sequence. Most of the motion is generated by the blazing flames in the foreground. The Construction Field is a relatively static video sequence depicting an excavator digging a foundation pit on a construction site. Apart from this, the only other movement is caused by several people walking in the background. Fountains is a video sequence showing a large fountain with several jets situated in a small square between trees and buildings in the background. The video was recorded with a still camera; hence only the water gushing from the fountain adds dynamism to the scene. Marathon is a video sequence shot from a bird’s eye view by an almost motionless camera. The scene depicts many people dressed in colorful raincoats competing in a race on a wet asphalt road during heavy rain. Runners is a video sequence capturing dozens of people in numbered jerseys racing on a road lined with trees. Even though the scene is filmed with a static camera, its considerable dynamism is added to by the fast movement of the runners and the wind in the leaves of the trees. Tall Buildings is a video sequence, recorded from a bird’s eye perspective, that captures the tallest Shanghai skyscrapers. The camera pans steadily, revealing a view of the driving cars in the distance, which are the only moving objects in the video. Wood is a video sequence recorded in bright daylight, picturing a sunlit forest. The camera moves with a fairly swift, panning motion. It is the most complex sequence, considering the amount of detail and motion in the video.First, all eight reference video sequences were subjected to chroma subsampling from the original YUV 4:4:4 to YUV 4:2:0 format. It is followed by a change in a bit of depth from 10 to 8 bits per channel. Afterward, these modified sequences were encoded by using two conventional standards, H.264 and H.265 at full HD and ultra HD resolutions. The bit rate ranged from 1 to 15 Mbps, employing the well-known FFmpeg software . A descrffmpeg -i Marathon_1920x1080_30fps_420_8bit_YUV.yuv -vcodec libx264 -x264-params keyint=15:min-keyint=15:bframes=3:b-adapt=1:bitrate=1M:vbv-maxrate=1M:vbv-bufsize=1M Marathon_1920x1080_30fps_420_8bit_H264_1M.ts.Subsequently, a local area network consisting of a streaming server and a streaming client was assembled to serve as a transmission channel for the previously encoded sequences. To simulate a lossy network connection, Clumsy  softwareApplying all possible combinations of compression parameters and PLR listed in L denotes the dynamic range of pixel values, and Objective quality measurement of the prepared video sequences was performed by using the MSU Video Quality Measurement Tool . Two welThe resulting SSIM value is determined by the weighted product of the brightness, contrast, and structure components asBy setting the weights The results obtained by using the SSIM metrics fall within the interval , where 1 expresses the best quality, which can be achieved only if all the compared frames are identical. It is a symmetric method, which means that the order of the reference and degraded video sequence is insignificant. Given that the SSIM is a full-reference metrics, it would seem logical to choose an uncompressed video sequence unimpaired by transmission over the IP network as a reference. The aim of our research was to investigate the effect of PLR on quality of video in different resolutions with various compression parameters. It was not directly about the combination of PLR and effect of compression. This is a reason why the corresponding sequence with identical bit rate undegraded by network transmission was always chosen as the reference sequence for the metrics. In this way, a total of, 9600 objective measurements were performed by using the SSIM method.x-axes of the graphs. The y-axes represent the measure of video quality evaluated by the SSIM metrics.In view of the fact that the purpose of this particular research is not examining the impact of the scene content on video quality, graphs contained in the paper present only the average quality ratings. It is the same over all types of sequences, with differing content for each codec and resolution evaluated. Furthermore, it should be noted that the results of the evaluation of each sequence that was streamed 10 times were also averaged. Because the video sequences unaffected by PLR encoded to both H.264 and H.265 in full HD and ultra HD, each bit rate of interest was used as a reference for the objective metrics. It is understandable that the quality of every sequence with 0% PLR was rated with an SSIM value of 1. Another common feature of 5—Excellent4—Good3—Fair2—Poor1—Bad.A subjective video-quality assessment was conducted to verify the findings that emerged from the analysis of the objective quality evaluation results. In addition to determining the strength of the correlation between subjective and objective measurement methods, the second reason for performing subjective tests was to monitor the combined impact of bit rate and PLR on respondents’ views of video quality. To ensure sufficient diversity of visual content while limiting the time requirements of test sessions, the four most diverse video sequences were selected for subjective quality assessment according to the SI-TI diagram, namely Campfire Party, Construction Field, Tall Buildings, and Wood. Considering that each compressed video was streamed and objectively evaluated 10 times, the sequence that achieved the median SSIM value was always chosen for the subjective tests. Bearing in mind all possible combinations of the given resolution, codec, bit rate, and packet loss rate, 560 test sequences were thus selected. The popular absolute category rating (ACR) was adopted for subjective quality assessment of the prepared video sequences. This single-stimulus method was chosen on the grounds that the test conditions are analogous to those under which a regular user watches multimedia content. The course of ACR assessment, described in ITU recommendation  is fasteN is a number of evaluated sequences, A total of 36 laymen with no visual impairment participated in the experiment, of whom 14 were women and 22 were men. The age bracket of respondents ranged from 16 to 62 years, and the average age was approximately 30 years. After the completion of the experiment, the elimination of outliers was necessary. For this purpose, a Pearson linear correlation coefficient (PLCC) was calculated between the evaluation results of all video sequences from one respondent and the average rating of each sequence, following the equationThe first step in processing the obtained subjective data was the calculation of the mean opinion score (MOS) of each evaluated video sequence. Statistical analysis of the first half of the evaluation results revealed that it is quite sufficient to inquire about the users’ opinion on the quality of video with a maximum PLR of 0.5% because after exceeding this value, the subjective quality was rated as poor at the utmost on the ACR scale. Between 0.5% and 1% PLR, the perceived quality further decreased on average by 0.28 and by a maximum of 0.45 MOS points. On that account, and for greater clarity, graphs included in this section show the development of subjectively perceived video quality with packet loss rates ranging from 0 to 0.5%.In order to calculate and investigate the correlation between subjective and objective evaluation results, the MOS values were shifted in a way such that the highest score of the given sequence was always 5 , and thux-axes, PLR within the narrowed limits 0–0.5% is plotted, and the y-axes represent the measure of video quality on the five-level MOS scale.Although this paper focuses mainly on the impact of PLR, the subjective method used made it possible to further examine the mixed impact of PLR and compression on subjectively perceived video quality. To illustrate this combined effect, it was sufficient to leave the MOS values unchanged in the graphical representation of the results. This can be seen in A common aspect of The essential distinction between the evaluation results of H.264 and H.265-encoded videos is the significantly more pronounced gap between the rating of lower bit rates (1 and 3 Mbps) compared to videos encoded at higher bit rates , which is evident on H.265 full HD sequences. This phenomenon is most eloquent when the simulated PLR reaches values from 0.1 to 0.2%. Another difference is a steeper decline in H.265 video quality, observable primarily at 10 and 15 Mbps. Unlike full HD videos, ratings of H.264-encoded ultra HD sequences diverged significantly from those at H.265 format. The only common aspects of x-axes. Each individual color curve represents a specific PLR. It is evident from these charts that subjective MOS values rise only until a certain value of bit rate is reached, and typically only at low PLR.If a certain packet loss rate in an error-prone network is anticipated, it may be convenient to get a better overview of how subjective quality changes as the bit rate increases or when other compression parameters are altered. For this reason, another four graphs were generated , with biBased on the subjective data analysis, it is viable to determine the most suitable combination of resolution, bit rate, and codec for use under different conditions. If the video content is transmitted over a reliable network, the only variable is the adverse effect of compression. In such a case, deploying the higher bit rate below a certain threshold will most certainly increase the perceived video quality. However, after exceeding this limit, respondents may be unable to distinguish between the quality of two video sequences at consecutive data rates, which is why the differences in ratings are narrowing with increasing bit rate. The highest average MOS of 4.833 was achieved by H.264 ultra HD sequences at 15 Mbps. Video sequences at both resolutions and codecs were considered better than good  at 5, 10, and 15Mbps. By using the H.265 coding format, even 3 Mbps videos surpassed this value. Our research shows that if the assumed PLR in the network is less than 0.1%, it is best to encode the video to H.265 at full HD resolution at 3 Mbps. The average perceived quality of such sequences reached the MOS value of 3.733. The advantage is that the transmission of video with these specifications requires almost the narrowest bandwidth, and is therefore also the fastest and most economical. Although the average MOS of 1 Mbps videos with the same parameters is only slightly lower with a value of 3.642, employing this bitrate is not advisable due to the substantial disparity between ratings of sequences with different content, which we observed during the experiments. For ultra HD video, the highest average MOS of 3.492 was reached by H.264 sequences at 10 Mbps, closely followed by MOS 3.402 of videos at 5 Mbps. If the connection is extremely unreliable with a possible PLR of 0.2% or more, we recommend using an H.264 coding format, ultra HD resolution and 5 Mbps data rate, as the development of video quality with such parameters is the most constant, starting at MOS 3.136 and ending at 2.646 when packet loss reaches 0.5%. For full HD video, the H.265 codec at 1 Mbps seems to be the most advantageous, as the MOS starts at 3.317, although it drops sharply afterward to 1.958 at 0.5% PLR. For greater clarity, The aim of this paper was to analyze the impact of PLR on quality of video in full HD and ultra HD resolution encoded to H.264 and H.265 format at a bit rate ranging from 1 to 15 Mbps. First, a dataset of 11,200 test video sequences with eight different types of content combining all the abovementioned parameters and simulated PLR in range of 0 to 1% was compiled. Based on the analysis of the results, several conclusions were drawn. As was expected, the video quality declined along with the increasing PLR, irrespective of resolution, codec, or bitrate used. In case of video unaffected by packet loss, both measured and perceived quality improved with rising bit rate. However, this did not apply to video sequences impaired by PLR. In fact, it appears that in the presence of PLR, video quality decreases with a steeper slope when a higher data rate is transmitted. This is caused by the fact that use of a higher bit rate leads to a larger file size of the video sequence to be streamed over the error-prone network, thus splitting the image information into more UDP packets. At the same PLR, more of these packets are discarded during transmission which results in more individual or clustered losses that can propagate in time and space, causing further video quality degradation. It stemmed from the further analysis of subjective MOS that even 0.1% loss generally has more prominent negative effect on perceived video quality than H.264 or H.265 compression artifacts, which means that in most cases, increasing the bit rate over a given threshold value results in greater video-quality degradation. Based on this observation, the paper also includes a recommendation of compression parameters for use when various levels of PLR are expected. Packet losses may generate errors in different types of data. It depends on which part of the packet is affected by the loss. If the header of the packet is affected, which is the worst case, it is not possible to decode the whole packet. However, our effort was not to analyze in detail which part of the packet is influenced by the loss because in real traffic it is not able to control which part of the packet is affected by the loss. Our effort was to take an average in the loss rate, which we achieved by multiple transmission sequences.


Thymus. It has been used as a therapeutic agent since ancient times. Thymus comprises numerous molecular species exhibiting diverse therapeutic properties that are dependent on their biologically active concentrations in the extracted oil. It is therefore not surprising that oils extracted from different thyme plants present different therapeutic properties. Furthermore, the phenophase of the same plant species has been shown to yield different anti-inflammatory properties. Given the proven efficacy of TO and the diversity of its constituents, a better understanding of the interactions of the various components is warranted. The aim of this review is to gather the latest research findings regarding TO and its components with respect to their immunomodulatory properties. An optimization of the various components has the potential to yield more effective thyme formulations with increased potency.Thyme oil (TO) is derived from the flowers of various plants belonging to the genus  Thymus serphyllum) is the wild relative of all cultivated species [Thymus vulgaris L.). Leaf morphology is one of the distinct features unique to the genus Thymus. The leaves are typically tiny (less than 1/8 inch long and 1/16 inch wide), narrow and elliptical, greenish-gray in color, and grouped in whorled phyllotaxy. Thyme flowers are white, yellow, or purple whorls that terminate branches. Some of the widely used cultivars of thymes for TO are Thymus rumidicus hispánicos, Thymus zygis, Thymus vulgaris, Thymus hyemalis, Thymus mastichina, Thymus citríodotus, Thymus corydothymus, Thymus loscossi, Thymus pipirella, and Thymus communis.Thymus is a perennial evergreen herb of the angiosperm plant family Lamiaceae (mint plant family) that has 350 species and 36 subspecies and is native to Europe, North Africa, and Asia . Because species . Garden Thymus vulgaris and Thymus magnus Nakai (Thyme oil (TO) is a complex mixture of at least 70 different species . Thymol us Nakai . It is aThymol is one of the main constituents of TO  within 8 days. In a different study, a combination of thymol and carvacrol reduced production of the inflammatory cytokines IL-25, IL-33, and Thymic Stromal Lymphopoietin (TSLP) in BEAS-2B-transformed human bronchial epithelial cells stimulated with chitin [Multiple studies highlight the anti-inflammatory properties of thymol ,19,20. Ind MCP-1 . Thymol h chitin . SHIP-1 A recent study utilizing U87 human malignant glioblastoma cells has shown that thymol induces apoptosis, increases Reactive Oxygen Species (ROS), and increases levels of the proapoptotic factors Bax and p53 . SimilarStreptococcus mutans by 50% [S. mutans by inducing autolysis, stress growth inhibition, and reduced biofilm formation. Currently, thymol-rich extracts are generally used as an expectorant in coughs associated with cold and also in dentistry as a disinfectant [E. coli. However, for E. faecalis and S. aureus, growth inhibition required a higher concentration. Antibacterial properties of thyme oil rich in thymol was also tested against the methicillin resistant (MRSA) strain [T. vulgaris to study the antimicrobial properties using MRSA strain S. aureus isolated from the oral cavity of patients suffering from periodontitis and pharyngitis. Thyme oil concentration of 0.01% (v/v) and 0.05% effectively reduced the growth up to 53% and 76%, respectively. The main components of volatile oil used in this research were phenolic monoterpenes, including thymol. In a similar study by Tohidpour et al. (2010), thymol extracted from T. vulgaris was more effective than essential oil from Eucalyptus globulus Labill in controlling the growth of MRSA [Pseudomonas aeruginosa even though the thymol level difference was nonsignificant . Recently, thymol-rich Thyme species are gaining attention for their antifungal properties. For example, studies on antifungal properties of thyme oil extract rich in thymol has been shown to be effective against growth of the fungal genus Cryptococcus, which is a pathogen responsible for cryptococcosis [Thymol has also been evaluated for its potential application as an antimicrobial agent. A thymol concentration of 100 μg/mL reduced viability of the dental caries causing bacteria s by 50% . Thymol nfectant . Thymol nfectant . The stu) strain ,30. Kryv of MRSA . Surpriscoccosis . In thiscoccosis .Recently, Liggri et al. (2023) have shown that both thymol and carvacrol bind to the novel mosquito protein AgamOBP5, an odorant-binding protein that is involved in the odorant perception process of mosquitoes . This waThymus capitatus plants was shown to be very high in carvacrol (79.9%) [Thymus vulgaris plants was shown to be much lower in carvacrol (1.56%) [2 and COX-2 levels were reduced with carvacrol.Carvacrol content in TO also varies significantly depending on the thyme species. TO derived from  (79.9%) . On the  (1.56%) . Similar (1.56%) . Mechani (1.56%) . IL-6, ICarvacrol showed analogous antitumoral properties as thymol in a study involving oral squamous carcinoma cells . Keap1/NThymus vulgaris L. has been shown to exhibit potent antibacterial activity against several strains of bacteria, including Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa [T. vulgaris L. had a minimum inhibitory concentration (MIC) of 0.5–1.5 mg/mL against these bacterial strains. Similar results have been observed by Gedikoğlu et al. (2019) in evaluating the antimicrobial properties of T. vulgaris L. on a series of gram-positive and gram-negative bacteria  [p < 0.05) higher antibacterial activity against bacteria than did the hydrodistilled essential oil extraction. Antibiotic-resistant pathogenic bacteria are gaining more attention and various plant derived species are being explored as alternative antimicrobial agents. A comparative study on essential oil extract from different herbs including T. vulgaris reported the synergistic effectiveness of carvacrol against 32 erythromycin-resistant Group A Streptococci [Streptococci. The same study evaluated the antibacterial properties of carvacrol alone and in combination with erythromycin. Surprisingly, carvacrol from T. vulgaris alone was effective in both treatment types’ ability to inhibit growth of Group A Streptococci, further enhancing the potential use of carvacrol as an effective phytotherapeutic agent against antibiotic-resistant bacteria [In addition to its anti-inflammatory properties, carvacrol has been extensively studied for its antibacterial properties. Several studies investigating the effects of carvacrol extracted from different Thyme species on various bacterial strains have been carried out. Carvacrol extracted from ruginosa . In theiimurium) . Surprisptococci . The Minbacteria . CarvacrThymus spp. show the lowest antibacterial activity compared to oxygenated compounds, especially phenol-type compounds such as thymol and carvacrol [Thyme spp. were also evaluated. Carvacrol extracted from T. zygis L. was found to be effective against several bacterial strains, including S. aureus and E. coli. An MIC of 0.16–0.63 mg/mL carvacrol extracted from T. zygis L. was found to be effective against controlling the growth of these bacterial strains. The antimicrobial properties of essential oil from the genus Thymus could be explained by their high percentage of phenol components. Carvacrol might interfere with the activity of cell wall enzymes, thus inhibiting bacterial growth by damaging their cell wall. A recent report investigating the antibacterial properties of carvacrol provided the possible mechanism of carvacrol against Streptococcus pyogenes [Among different chemotypes, hydrocarbon monoterpenes in essential oils extracted from arvacrol . The antpyogenes . CarvacrThymus cultivars as antifungal agents has been reported recently [T. vulgaris against eight yeast species and eight filamentous fungi isolated from mucocutaneous fungal infection pathogens for skin diseases. For this study, TO was extracted from fresh leaves and floral heads. Out of 25 bioactive compounds in the thyme oil, carvacrol (56.8%) was detected in high amounts, followed by p-cymene (12.8%), γ-terpinene (11.17%), and thymol (3.99%). A series of fungal species were used for the sensitivity assay, which included different strains of yeast , and filamentous fungus . Out of three concentrations , TO concentration of 60 μL was effective against all tested yeast strains as compared to the positive control (1% Hexamidine). Candida tropicalis and C. parapsilosis were the most vulnerable strains to the TO, with zones of inhibition of 50 mm and 60 mm. Among filamentous fungi, TO was more effective against Aspergillus terreus and A. fumigatus . Similar antifungal properties of carvacrol against Candida tropicalis were reported by other studies as well [Thymus rich in monoterpenic alcohols and/or volatile phenols [Botrytis cinerea, a primary pathogen causing stem and fruit rot during pre- and postharvest of ornamental crops, fruits, and vegetables [Thymus species such as T. zygis and T. vulgaris, with higher quantities of phenols, also demonstrated a wide spectrum of inhibitory growth against a range of pathogenic filamentous fungi and yeasts, with decreased sensibility to antifungal drug [The potential application of carvacrol from various recently ,48,49,50 as well ,52. In a phenols ,54. Anotgetables . Out of gal drug ,54,55. HP-cymene is typically found at lower concentrations in TO compared to thymol and is a component of other essential oils including cinnamon and cumin . P-cymenP-cymene’s antitumoral effects were reported in a high-fat diet colorectal cancer rat model . A signiThymus vulgaris have a much lower content in relation to the Thymus capitatus species [γ-Terpinene belongs to a group of isomeric compounds referred to as monoterpenes. Their difference lies in the position of the two carbon–carbon double bonds see . γ-Terpi species ,34. It iThymbra capitata TO and, by extension, its components were mostly attributed to p-cymene and carvacrol where strong synergism was reported against Gardnerella spp [2. Inhibition of the COX-2 enzyme with nimeluside (selective COX-2 inhibitor) abolished the IL-10 increase. Furthermore, with diminished IL-10 production, the inhibition of IL-1β and IL-6 was lost. γ-Terpinee in IL-10-deficient mice did not produce any inhibition on IL-1β and IL-6, suggesting the PGE2/IL-10 pathway as a mechanism for its anti-inflammation. This pathway is not utilized by carvacrol, thymol, and p-cymene and makes γ-terpinene unique particularly in terms of the induction of IL-10.There is much less research on γ-Terpinene compared to thymol, carvacrol, and p-cymene. The antimicrobial properties of ella spp . Nonetheella spp . InteresLinalool is another constituent of TO, but with lower prevalence than thymol, carvacrol, and p-cymene. A terpene alcohol, linalool is found in a variety of flowers and seeds and their essential oils . LinalooMultiple studies have investigated linalool’s anti-inflammatory qualities in a variety of systems. Cigarette smoke-induced inflammation was inhibited by linalool in mice . ReductiProtective effects of linalool have been reported in neurodegenerative animal models as well . The aniThyme oil (TO) has a proven record of therapeutic properties and characterized in detail anti-inflammatory mechanisms see . HoweverIn addition, future research directions relating to TO and its derivatives may include synergistic formulations with other drugs. For example, the anti-inflammatory properties of thymol, carvacrol, p-cymene, γ-terpinene, and linalool can be used in conjunction with widely used corticosteroids. Formulations composed of synthetic corticosteroids and TO constituents may allow for lower concentrations of the synthetic component and achieve a reduction in side effects typically seen when using only the synthetic drugs. A similar approach may be employed with antibiotics where the use of TO components along with antibiotics may permit a reduction in concentration of the synthetic antibiotic and a reduction in side effects and antibiotic resistance. This strategy has been used for many years now with clavulanic acid and amoxicillin. Another future direction worth investigating is the use of carvacrol and thymol in combination with known synthetic insect repellants where the formulation will permit a lower concentration of the synthetic repellants. The natural scent of carvacrol and thymol will be an added benefit.In conclusion, there is ample scientific evidence that TO and its constituents have diverse therapeutic properties. However, it is unlikely that they can compete or replace synthetic drugs with similar and often more potent properties. Future research should focus on optimizing formulations of TO constituents by themselves and with synthetic drugs to maximize their potency while reducing their toxicity.


Drosophila only encodes one member of the family, Bonus. Bonus has been implicated in embryonic development and organogenesis and shown to regulate several signaling pathways, however, its targets and mechanism of action remained poorly understood. We found that knockdown of Bonus in early oogenesis results in severe defects in ovarian development and in ectopic expression of genes that are normally repressed in the germline, demonstrating its essential function in the ovary. Recruitment of Bonus to chromatin leads to silencing associated with accumulation of the repressive H3K9me3 mark. We show that Bonus associates with the histone methyltransferase SetDB1 and the chromatin remodeler NuRD and depletion of either component releases Bonus-induced repression. We further established that Bonus is SUMOylated at a single site at its N-terminus that is conserved among insects and this modification is indispensable for Bonus’s repressive activity. SUMOylation influences Bonus’s subnuclear localization, its association with chromatin and interaction with SetDB1. Finally, we showed that Bonus SUMOylation is mediated by the SUMO E3-ligase Su(var)2–10, revealing that although SUMOylation of TIF1 proteins is conserved between insects and mammals, both the mechanism and specific site of modification is different in the two taxa. Together, our work identified Bonus as a regulator of tissue-specific gene expression and revealed the importance of SUMOylation as a regulator of complex formation in the context of transcriptional repression.The conserved family of Transcription Intermediary Factors (TIF1) proteins consists of key transcriptional regulators that control transcription of target genes by modulating chromatin state. Unlike mammals that have four TIF1 members,  Drosophila, making it an attractive model to understand the conserved functions of TIF1 proteins.Epigenetic regulation of gene expression is an essential mechanism that guides cell differentiation during development. The post-translational modifications of chromatin proteins act in combination with various chromatin-remodeling proteins to mediate changes in transcriptional activities and chromatin structure 2–10, in contrast to mammalian KAP-1 that auto-SUMOylates itself. Our results identify Bon as a regulator of tissue-specific gene expression and highlight the universal function of SUMOylation as a regulator of complex formation in the context of transcriptional repression. On the other hand, our work suggests that SUMOylation of bon gene encodes a nuclear protein that is expressed throughout development with high level of expression in several tissues including the brain, gut, and ovaries . Using the maternal tubulin-Gal4  driver, we found by RT-qPCR (quantitative reverse transcription PCR) that two distinct shRNAs targeting bon led to 75% and 88% reduction in ovarian Bon expression, respectively  did not result in significant changes in ovarian morphology compared to controls  flies that lack later stages of oogenesis and compared them to their age-matched siblings that lack the shRNA, and for MT-gal4 we used 1- to 2-old flies that express either shRNA against bon or the white gene, which is not expressed in the germline. Thus, in both cases, GLKD and control flies had the same age and similar ovary size. As the mammalian homolog of Bon, KAP-1, plays a central role in repression of many transposable elements (TEs) through its function as co-repressor for multiple KRAB-ZFPs that recognize TEs sequences, we analyzed expression of both host genes and TEs.To investigate the effect of Bon depletion on gene expression in the female germline, we performed transcriptome profiling using RNA sequencing (RNA-seq) analysis. We tested the effects of loss of Bon in both early and later stages of oogenesis using the nos-Gal4-driven shRNA, only 6 out of 207 (~3%) TE families present in the Drosophila genome significantly increased their expression more than twofold , Sleuth) (Most TEs families were not affected by Bon depletion using either driver. Using the  Sleuth)  and none Sleuth) . This phMT-Gal4 revealed 1769 genes that were differentially expressed , with 231 genes (~13.6%) showing more than twofold increase, while 72 genes (~4.2%) showed more than a twofold decrease in mRNA level . GO analysis identified enrichment of genes from 27 biological process in the set of Bon-repressed genes  analysis of genes strongly upregulated upon ed genes . These ied genes .rbp6, CG34353, and ple, which are highly expressed in the head, and pst, which is highly expressed in the gut, to confirm that germline depletion of Bon triggers their ectopic activation. No signal for these genes was detected in wild-type ovaries, while abundant rbp6, CG34353, and pst transcripts were identified in germ cells upon MT-Gal4>Bon GLKD  for selected upregulated genes including Bon GLKD . Surprisar cells . Overallple gene in the somatic follicular cells some of these effects might be indirect and even mediated by intercellular signaling. To test the ability of Bon to directly induce transcriptional silencing, we took advantage of a tethering approach in which Bon is recruited to a reporter locus via binding to nascent transcripts . Global ChIP-seq analysis revealed that many Bon-dependent genes show low or no H3K9me3 signal in control ovaries and no change upon Bon depletion, hence might be secondary targets , respectively , an inhibitor of SUMO-specific deconjugating enzymes. Western blot revealed the presence of unmodified and single SUMO-modified forms of Bon  and K20 (IKQE), are conforming to the canonical consensus site for SUMOylation, ΨKxD/E, whereas the third one, K763, resides in a noncanonical motif, LKSP 2–10 protein was identified as a Bon interactor in S2 cells . We show for Bon . To expl for Bon . Second, for Bon . Finally for Bon . CombineDrosophila, is ubiquitously expressed throughout development and previous studies have demonstrated its role in the development of several organs and tissues, particularly the nervous system , which recognize their target DNA sequences – primarily various endogenous retroviruses and other types of TEs – via their zinc-finger domains . HoweverDrosophila Bon and mammalian TIF1 members, such as KAP-1. Similar to KAP-1, Bon induces transcriptional repression associated with accumulation of the H3K9me3 repressive histone mark  and in fact are located in different regions in Bon and KAP-1. Bon is SUMOylated at a single residue, K20, close to its N terminus  and thisThe second important difference is the molecular mechanism of SUMOylation of TIF1 members in insects and vertebrates. The PHD domain of mammalian KAP-1 functions as a SUMO E3-ligase to induce modification of the adjacent bromodomain . ImportaDrosophila TIF1 factor, Bon, in repression of tissue-specific genes in the germline and suggests that Bon SUMOylation at a single site by the SUMO E3-ligase Su(var)2–10 is critical for its role as a transcriptional repressor.In conclusion, our study reveals an essential function of Su(var)2–10 , Rpd3 , Mi-2  and white  and nos-Gal4;UAS-Cas9 (BDSC #54593) were obtained from the Bloomington Drosophila Stock Center. The fly line expressing sgRNAs targeting bon (VDRC #341851) was obtained from the Vienna Drosophila Resource Center. Fly lines UASp-mKate2-4xBoxB-K10polyA, UASp-λN-GFP-eGFP control, UASp-λN-GFP-Su(var)–10, shSmt3 were described previously . The expression of constructs was driven by maternal alpha-tubulin67C-Gal4  (BDSC #7063), nos-Gal4 (BDSC #4937), or bam-Gal4 (BDSC #80579) drivers.All fly stocks and crosses were raised at 24°C. One- to two-day-old females were put on yeast for 1 day prior to dissection. Females from crosses with GLKD at early stages of oogenesis and respective control were 0–1 days old and were dissected right away. The following stocks were used: stocks with shRNAs targeting eviously . shSetDBeviously  was ligaeviously  and thenDrosophila lines expressing UASP-λN-GFP-Bonus and UASP-λN-GFP-Bonus[3KR] under the control of the MT-Gal4 driver were dissected in ice-cold phosphate-buffered saline (PBS) and then fixed in PBST solution  supplemented with 4% formaldehyde for 20 min at room temperature with end-to-end rotation. Samples were washed three times 10 min with PBST and mounted in SlowFade Gold antifade Mountant with DAPI. Seven to fifteen pairs of ovaries from Drosophila Oregon-R flies and lines with GLKD of Bon under the control of the nos-Gal4 or bam + nos drivers were fixed in PBST supplemented with 4% formaldehyde for 20 min at room temperature with rotation and then washed three times 10 min with PBST. Fixed ovaries were incubated for 30 min with PBX , and blocked in 5% normal goat serum (NGS) in PBX for 1 hr at room temperature. Samples were incubated with primary antibody in 3% NGS in PBX overnight at 4°C with rotation, followed by three washes in PBX solution for 10 min, and an overnight incubation with secondary antibody in 3% NGS in PBX at 4°C with rotation in the dark. After three washes in PBX, SlowFade Gold antifade Mountant with DAPI was added to the samples. Confocal images were acquired with a Zeiss LSM 800 using a ×63 oil immersion objective and were processed using Fiji. Primary antibodies to Vasa , to α-spectrin , and to Bon (a gift from Hugo Bellen) were used. Secondary antibodies were anti-mouse Alexa Fluor488, anti-rat Alexa Fluor546 (Invitrogen), and anti-guinea pig Cy3 (Jackson ImmunoResearch Inc).Seven to fifteen pairs of ovaries from TUNEL analysis was performed using In Situ ‘Cell Death Detection Kit’ (TMR Red) .molecularinstruments.org) for bon (unique identifier: 4165/E324), ple (unique identifier: 4324/E516), Rbp6 (unique identifier: 4408/E662), pst (unique identifier: 4408/E660), and CG34353 (unique identifier: 4408/E658) transcripts. RNA in situ HCR v3.0 was performed according to the manufacturer’s instructions for generic samples in solution.For RNA in situ HCR, probes, amplifiers, and buffers were purchased from Molecular Instruments  were cultured at 25°C in Schneider’s Drosophila Medium supplemented with 10% heat-inactivated fetal bovine serum and 1× penicillin–streptomycin.S2 cells were transfected with plasmids encoding HA-, GFP-, and FLAG-tagged proteins under the control of the Actin promoter using TransIT-LT1 reagent (Mirus). 24–40 hr after transfection, cells were collected and resuspended in lysis buffer  and Complete Protease Inhibitor Cocktail (Roche)). The cell lysate was incubated on ice for 30 min, centrifuged and the supernatant collected. The supernatant was incubated with magnetic agarose GFP-Trap beads (Chromotek) for 2 hr at 4°C with end-to-end rotation. Beads were washed three to four times for 10 min with wash buffer  and boiled in 2× Laemmli buffer for 5 min at 95°C. The eluate was used for western blot analysis. For detection of SUMO-modified Bon, cells were lysed in RIPA (Radioimmunoprecipitation assay)-like buffer , and washed in high salt wash buffer . For treatment with SUMO protease, cells were lysed in RIPA-like buffer without NEM and with in-house made SENP2 protease .MT-Gal4 driver were lysed and dounced in 500 μl lysis buffer ). The ovary lysate was incubated on ice for 30 min, then centrifuged and the supernatant collected. The supernatant was incubated with magnetic agarose GFP-Trap beads (Chromotek) for 2–3 hr at 4°C with end-to-end rotation. Beads were washed four times ≥10 min at 4°C with ovary high salt wash buffer . Washed beads were further in 2× Laemmli buffer for 5 min at 95°C, and the eluate was analyzed by western blotting.For detection of SUMO-modified Bon, 70–90 pairs of dissected ovaries co-expressing Flag-tagged SUMO and λN-GFP-Bonus or λN-GFP-Bonus[3KR] under the control of the 2, 300 mM sucrose, 0.1% Triton X-100, 1 mM DTT (Dithiothreitol), cOmplete Protease Inhibitor Cocktail (Roche)). A small fraction of lysate was saved as whole cell lysate for western blot analysis. For subcellular fractionation 2 volumes of buffer ‘B’ ) were added to the lysate. The lysate was incubated for 5 min on ice and then centrifuged at 5900 × g for 15 min at 4°C. The supernatant was transferred to a new tube, centrifuged at 19,000 × g for 10 min 4°C, and saved as cytoplasmic fraction for western blot analysis. The cell pellet was resuspended in ‘E2’ buffer , 0.5 mM EGTA (ethylene glycol-bis(β-aminoethyl ether)-N,N,N′,N′-tetraacetic acid), and cOmplete Protease Inhibitor Cocktail (Roche)) and centrifuged at 1500 × g for 2 min at 4C. The supernatant was transferred to a new tube, centrifuged at 19,000 × g for 10 min 4°C, and saved as nuclear fraction for western blot analysis. The pellet was once washed in E2 buffer, then resuspended in E2 buffer and incubated for 10 min at 4°C, followed by centrifugation at 1500 × g for 2 min at 4°C. For chromatin extraction, the pellet was resuspended in ‘E3’ buffer ) and then sonicated for 5 min at high setting with 30sON/30sOFF in a Bioruptor sonicator (Diagenode) and centrifuged for 5 min at 19,000 × g at 4°C. The supernatant was saved as chromatin fraction for western blot analysis. Protein concentration of all fractions was measured and further all saved fractions were boiled with 1× final concentration of Laemmli buffer for 5 min at 95°C and analyzed by western blotting.For whole ovaries and subcellular compartment extraction, 30–40 pairs of fly ovaries expressing λN-GFP-Bonus or λN-GFP-Bonus[3KR] were lysed and dounced in ice-cold ‘AT’ buffer (15 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid)–NaOH pH 7.6, 10 mM NaCl, 5 mM MgOAc, 3 mM CaClProteins were separated by SDS–PAGE gel electrophoresis and transferred to a 0.45-μm nitrocellulose membrane (Bio-Rad) according to standard procedures. The membrane was blocked with 5% milk or with 0.2% I-block (Invitrogen) in PBST  for 1 hr. The membrane was incubated with primary antibodies for 2 hr at room temperature or overnight at 4°C, followed by 3× washes for 5 min in PBST and incubation with secondary antibodies for 1 hr at room temperature. The membrane was washed three times for 5 min with PBST and then imaged with Odyssey system (Li-Cor). When primary antibody was HRP (horseradish peroxidase) conjugated, the membrane was washed 3 × 5 min with PBST, incubated with the HRP substrate, and X-ray film developed on an X-Ray Film Processor (Konica Minolta). The following antibodies were used: HRP-conjugated anti-FLAG , mouse anti-FLAG , rabbit polyclonal anti-GFP , rabbit conjugated, the membrane was washed 3 × 5 min with PBST, incubated with the HRP substrate, and X-ray film developed on an X-Ray Film Processor (Konica Minolta). The following antibodies were used: HRP-conjugated anti-FLAG , mouse anti-FLAG , rabbit polyclonal anti-GFP , rabbit For RNA extraction 10–20 pairs of dissected ovaries were homogenized in TRIzol (Invitrogen), RNA extracted, isopropanol precipitated, and treated with DNaseI (Invitrogen) according to the manufacturer’s instructions. Reverse transcription was performed using random hexamer oligonucleotides with Superscript III Reverse Transcriptase (Invitrogen). qPCR was performed on a Mastercyclerep realplex PCR machine (Eppendorf). Three biological replicates per genotype were used for all RT-qPCR experiments. Target expression was normalized to rp49 mRNA expression. The data were visualized using Python 3 via JupyterLab. Primers used for qPCR analysis are listed in nos-Gal4 (and matched siblings that lack the shRNA as control). Total RNA from line with Bon GLKD driven by MT-Gal4 (and control flies that express an shRNA against the white gene) was depleted of ribosomal RNA with the Zymo-Seq RiboFree Total RNA Library Kit . RNA-seq libraries were made using the NEBNext Ultra II Directional RNA Library Prep kit for Illumina  according to the manufacturer’s instructions. Libraries were sequenced on the Illumina HiSeq 2500 platform. To quantify expression level of protein-coding genes and TEs, RNA-seq libraries were pseudoaligned to the D. melanogaster transcriptome  and transposon consensuses  using bowtie1 (v.1.2.2) allowing two mismatches and single mapping position. Tracks were generated using deepTools (v.3.5.1) bamCoverage function with 10 bp bin sizes.For RNA-seq libraries, total RNA was extracted from fly ovaries using TRIzol reagent. PolyA+ selection was performed using an NEBNext Poly(A) mRNA Magnetic Isolation Module  for total RNA from lines with Bon GLKD driven by nos-Gal4 . The data visualization was performed using the ‘ggplot2’ R package.GO biological-process term enrichment analysis was performed on the genes that were significantly derepressed upon Bon GLKD driven by g, and supernatants collected. The supernatants were first precleared for 2 hr at 4°C using Protein G Dynabeads (Invitrogen). Precleared samples were immunoprecipitated with anti-H3K9me3  antibodies for 3–5 hr at 4°C, then 50 μl Protein G Dynabeads were added, and samples were further incubated overnight at 4°C. Beads were washed 3 × 10 min in LiCL buffer, followed by proteinase K treatment for 2 hr at 55°C and then overnight at 65°C. DNA was extracted by standard phenol–chloroform extraction. ChIP-qPCR was performed on the Mastercyclerep realplex PCR machine (Eppendorf). All ChIPs were normalized to respective inputs and to control region rp49. The data were visualized using Python 3 via JupyterLab. Primers used for qPCR analysis are listed in ChIP experiments were performed in two biological replicas as previously described . In brieD. melanogaster genome (dm6) using bowtie1 (v.1.2.2) allowing two mismatches and single mapping position. Genome coverage tracks were generated using deepTools (v.3.5.1) bamCoverage function with 10 bp bin sizes. ChIP signal was normalized to input counts by calculating cpm (counts per million) using the deepTools bamCompare function with 50 bp bin sizes (ChIP/Input). Heatmaps were generated with deepTools plotHeatmap using normalized (ChIP/Input) BigWig files.ChIP-seq libraries were prepared using NEBNext Ultra DNA Library Prep Kit Illumina (NEB) and sequenced on the Illumina HiSeq 2500 platform (PE 50 bp). After removal of the adaptors, reads with a minimal length of 18 nucleotides were aligned to the nos-Gal4  nonredundant protein database with the Position-Specific Iterated BLAST (PSI-BLAST) program. Orthologs of Bon in other Drosophila species and some insects were identified based on high sequence similarity. Multiple sequence alignment was performed using the ClustalW program. The species distribution of the orthologs was visualized using SeaView v5.0.5. Phylogenetic tree was built with ClustalW and iTOL v6 software.The  important study advances our knowledge of Drosophila Bonus, the sole ortholog of the mammalian transcriptional regulator Tif1. Solid evidence, both in vivo and in vitro, shows how SUMOylation controls the function of the Bonus protein and what the impact of SUMOylation on the function of Bonus protein in the ovary is.This  Summary:Drosophila model system for understanding how the activity of Tif1 proteins is modified by SUMO. The authors convincingly show that Bonus, like homologous mammalian Tif1 proteins, is a repressor, and that it interacts with other co-repressors Mi-2/NuRD and SetDB1 in Drosophia ovaries and S2 cells. They also show that Bonus is SUMOylated by Su(var)2-10 on one lysine at its N-terminus to promote its interaction with SetDB1. By combining biochemistry with an elegant reporter gene approach, they show that SUMOylation is important for Bonus interaction with SetDB1, and that this SUMO-dependent interaction triggers high levels of H3K9me3 deposition and gene silencing. While there are still major questions of how SUMO molecularly promotes this process, the authors conducted several experiments that will guide future work. For example, they showed that SUMOylation likely indirectly promotes Bon interaction with SetDB1 because mostly unSUMOylated Bon copurifies with SetDB1. They also show that SUMOylated and unSUMOylated Bon differentially localize within the cell, and preventing Bon SUMOylation alters its subcellular localization. These important experiments disfavor a simple model where SUMO bridges the Bon/SetDB1 interaction and hint at a more complex multi-step assembly process that regulates Bon-dependent transcriptional silencing.This important study from Godneeva et al. establishes a  Summary:Drosophila ortholog of the TIF1 family of mammalian transcriptional regulators. Bon has been implicated in several developmental programs, however the molecular details of its regulation have not been well understood. Here, the authors reveal the requirement of Bon in oogenesis, thus establishing a previously unknown biological function for this protein. Furthermore, careful molecular analysis convincingly established the role of Bon in transcriptional repression. This repressor function requires interactions with the NuRD complex and histone methyltransferase SetDB1, as well as sumoylation of Bon by the E3 SUMO ligase Su(var)2-10. Overall, this work represents a significant advance in our understanding of the functions and regulation of Bon and, more generally, the TIF1 family. Since Bon is the only TIF1 family member in Drosophila, the regulatory mechanisms delineated in this study may represent the prototypical and important modes of regulation of this protein family. The presented data are rigorous and convincing. As discussed below, this study can be strengthened by a demonstration of a direct association of Bon with its target genes, and by analysis of the biological consequences of the K20R mutation.The authors analyze the functions and regulation of Bon, the sole Strengths:1. This study identified the requirement for Bon in oogenesis, a previously unknown function for this protein.2. Identified Bon target genes that are normally repressed in the ovary, and showed that the repression mechanism involves the repressive histone modification mark H3K9me3 deposition on at least some targets.3. Showed that Bon physically interacts with the components of the NuRD complex and SetDB1. These protein complexes are likely mediating Bon-dependent repression.4. Identified Bon sumoylation site (K20) that is conserved in insects. This site is required for repression in a tethering transcriptional reporter assay, and SUMO itself is required for repression and interaction with SetDB1. Interestingly, the K20-mutant Bon is mislocalized in the nucleus in distinct puncta.5. Showed that Su(var)2-10 is a SUMO E3 ligase for Bon and that Su(var)2-10 is required for Bon-mediated repression.Weaknesses:The study would be strengthened by demonstrating a direct recruitment of Bon to the target genes identified by RNA-seq. - It appears that the authors have attempted such an experiment, but it was not successful due to the current technical limitations, as the authors describe in their rebuttal.The second area where the manuscript can be improved is to analyze the biological function of the K20R mutant Bonus protein. The molecular data suggest that this residue is important for function, and it would be important to confirm this in vivo. - Fig. 5G indeed shows that the 3KR mutant is deficient in inducing repression, which partially addresses this concern. In the future, it would be interesting to test if the single K20R is similarly deficient, and to analyze any resulting phenotypes. The following is the authors’ response to the original reviews.Reviewer #1 (Public Review):Summary:Drosophila model system for understanding how the activity of Tif1 proteins is modified by SUMO. The authors nicely show that Bonus, like homologous mammalian Tif1 proteins, is a repressor, and that it interacts with other co-repressors Mi-2/NuRD and setdb1 in Drosophila ovaries and S2 cells. They also show that Bonus is SUMOylated by Su(var)2-10 on at least one lysine at its N-terminus to promote its interaction with setdb1. By combining nice biochemistry with an elegant reporter gene approach, they show that SUMOylation is important for Bonus interaction with setdb1, and that this SUMO-dependent interaction triggers high levels of H3K9me3 deposition and gene silencing. While there are still major questions of how SUMO molecularly promotes this process, this study is a valuable first step that opens the door for interesting future experimentation.This important study from Godneeva et al. establishes a Major Point:The RNAseq and ChIPseq data is not available. This is critical for the review of the paper and would help the readers and reviewers interpret the Bonus mutant phenotype and its mechanism of repressing genes.The sequencing data have been deposited to the NCBI GEO archive. The accession number for all other RNA-seq and ChIP-seq data reported in this paper is GEO: GSE241375.1. The author's conclusion that Bonus SUMOylation is "essential for its chromatin localization" is not supported by the data. Figure 5F shows less 3KR mutant in the chromatin fraction but there is still significant signal.We appreciate the reviewer's feedback and agree that the term "essential" was not appropriate in this context. We have revised the manuscript to replace "essential" with "contributes to" to accurately reflect our findings.1. The author's conclusion that Bonus is SUMOylated at a single site close to its N-terminus is not necessarily true. In several SUMO and Bonus blots throughout the paper , there are >2 differentially migrating species that could represent more than one SUMO added to Bonus. While the single K20R mutation eliminates all of these species in Fig 5C, it is possible that K20R SUMOylation is required for additional SUMOylation events on other residues. One way to determine if Bonus is SUMOylated on multiple sites is to add recombinant SUMO protease to the extract and see if multiple higher molecular weight bands collapse into a single migrating species (implying multiple SUMOs) or multiple migrating species .We appreciate the suggestion made by the reviewer. While we acknowledge the presence of occasional multiple bands in SUMO Western blots, the predominant pattern is the presence of unmodified Bon and a single additional band corresponding to SUMO-modified Bon. To investigate the possibility of multi-site SUMOylation, we performed requested experiment where we added SENP2 SUMO protease to the extract and checked Bon's SUMOylation. In the presence of NEM, we observed the unmodified form of Bon, as well as a single additional band representing a SUMO-modified form of Bon. Following SENP2 SUMO protease treatment, SUMOylation form of Bon was completely abolished in all samples, leaving only the unmodified Bon band . This indicates that Bon is not SUMOylated on multiple sites and that the observed differential migration species likely result from other factors affecting gel migration.1. The authors state that most upregulated genes in BonusGLKD are not highly enriched in H3K9me3. The heatmap in figure 3D is not an ideal presentation of this argument. The authors should show an example of what the signal on a highly enriched gene looks like for comparison. The authors also argue that because most upregulated genes in BonusGLKD are not highly enriched in H3K9me3, they must be indirectly repressed. Another possibility is that bonus-mediated H3K9me3 is only important (and present) during early nurse cell differentiation and is later lost and dispensable during the rapid endocycles. After bonus establishes repression though H3K9me3, it might be maintained through bonus-Mi2/Nurd, something else, or nothing at all. The authors could discuss this possibility or perform H3K9me3 ChIP during cyst formation and early nurse cell differentiation rather than in whole ovaries, which are enriched for later stages.We thank the reviewer for their thoughtful comments and suggestions. In our revised manuscript we have included the tracks of gene that is highly enriched in H3K9me3 but remain unchanged upon Bon GLKD . This addition allows for a visual comparison and better supports our argument that majority of genes upregulated in Bon GLKD are not enriched in H3K9me3 mark. We also appreciate the reviewer's suggestion regarding the potential temporal dynamics of Bon-mediated H3K9me3. It is indeed possible that Bon's role in establishing H3K9me3 might be more prominent during early nurse cell differentiation and less critical in later stages. We included discussion of this possibility in revised manuscript. To further explore it would be valuable to perform H3K9me3 ChIP during cyst formation and early nurse cell differentiation. However, given the limitations of our current resources and time limitations, we were unable to perform these experiments for the revised manuscript.1. The BonusGLKD RNAseq analysis is underwhelming. The conclusion that "Bonus represses tissue-specific genes" has limited value. Every gene that is not expressed in ovaries is "tissue-specific." What subset of tissue-specific genes does Bonus repress? What common features do these genes have and how do they compare to other sets of tissue-specific genes, such as those reportedly repressed by setdb1, Polycomb proteins, small ovary, l(3)mbt, and stonewall . Comparing these available data sets could help the authors understand the mechanism of Bonus repression and how BonusGLKD leads to sterility. The authors could also further analyze the differences between nos-Gal4 and MT-Gal4 to better understand why nos- but not MT-driven knockdown is sterile.We appreciate the reviewer's feedback regarding the RNA-seq analysis and acknowledge the importance of identifying the specific subset of tissue-specific genes. The Figure 2C shows specifictissues where genes derepressed upon Bon GLKD are normally expressed. These are tissues/organs such as the head, digestive system, and nervous system. The reviewer's suggestion to compare our findings with existing datasets are valid and could indeed provide a more comprehensive understanding of Bon repression and its implications in female germ cells. However, many of the published datasets are based on mutant fly lines or use different GAL4 drivers to induce knockdowns, making direct comparisons challenging. We have conducted a preliminary analysis of available data, specifically nos-Gal4>SetDB1KD (GSE109852), and identified an overlap of 135 genes out of the 464 genes upregulated upon nos-Gal4>BonusKD with those affected by SetDB1 knockdown. We have included this result in the revised manuscript.Main Study Limitations:1. It is unclear which genes are directly vs indirectly regulated by bonus, which makes it difficult to understand Bonus's repressive mechanism. Several lines of experiments could help resolve this issue. (1) Bonus ChIPseq, which the authors mentioned was difficult. (2) RNAseq of BonusGLKD rescued with KR3 mutation. This would help separate SUMO/setdb1-dependent regulation from Mi-2 dependent regulation. Similarly, comparing differentially expressed genes in Su(var)2-10GLKD, setdb1GLKD, 3KR rescue, and MI-2 GLKD could identify overlapping targets and help refine how bonus represses subsets of genes through these different corepressors.We appreciate the reviewer's suggestions and agree that discrimination between direct and indirect Bon targets should be the next step in understanding Bon repressive mechanism. We have previously attempted to determine Bon direct targets using ChIP-seq approach. However, despite our multiple efforts using both native Bon antibodies and GFP-tagged Bon fly lines, analysis of ChIP-seq data did not reveal specific enrichment indicating that Bon – similar to many other chromatin-bound proteins – are not amenable to ChIP. The recommendation for RNA-seq analysis of Bon GLKD rescued with the 3KR mutation is valuable, and we will certainly consider it for future investigations.We compared differentially expressed genes in Su(var)2-10 GLKD and Mi-2 GLKD and found limited overlap: out of the 231 genes affected by Bon GLKD, 39 genes were affected in Mi-2 GLKD and 42 in Su(var)2-10 GLKD. We acknowledge the importance of understanding which genes are directly or indirectly regulated by Bon and the potential for further experiments to address this question.1. The paper falls short in discussing how SUMO might promote repression. This is important when considering the conservation (of lack thereof) of SUMOylation sites in Tif1 proteins in distantly related animals. One piece of data that was not discussed is the apparent localization of SUMOylated bonus in the cytoplasmic fraction of the blot in Figure 5F. Su(var)2-10 is mostly a nuclear protein, so is bonus SUMOylated in the nucleus and then exported to the cytoplasm? Also, setdb1 is a nuclear protein, so it is unlikely that the SUMOylated bonus directly interacts with setdb1 on target genes. Together with Fig 5E (unSUMOylatable Bonus aggregates in the nucleus), one could make a model where SUMO solubilizes bonus (perhaps by disassembling aggregates) and indirectly allows it to associate with setdb1 and chromatin. It is also important to note that in Figure 5I, the K3R mutation appears to lessen but not eliminate Bonus interaction with setdb1. This data again disfavors a model where SUMO establishes an interaction interface between setdb1 and Bonus. To determine which form of Bonus interacts with setdb1, the authors could perform a setdb1 pulldown and monitor the SUMOylation state of coIPed Bonus through mobility shift. If mostly unSUMOylated bonus interacts with setdb1, and SUMO indirectly promotes Bonus interaction with setdb1 (perhaps by disassembling Bonus aggregates), then the precise locations of Bonus SUMOylation sites could more easily shift during evolution, disfavoring the author's convergent evolution hypothesis.We appreciate the reviewer's valuable feedback. Regarding the observation of SUMOylated Bon in the cytoplasmic fraction in Figure 5F, we recognize its significance. This finding has prompted us to consider a model in which SUMOylation may play a role in translocating Bon from the nucleus to the cytoplasm, potentially influencing interactions with SetDB1 and chromatin indirectly. Furthermore, Figure 5I which shows only a partial reduction in Bon-SetDB1 interaction with the 3KR mutation, suggests that SUMO may not be the primary mediator of this interaction. We recognize the need for further investigations to clarify SUMO's exact role in this context. In response to the reviewer's suggestion, we conducted SetDB1 pulldown experiments in S2 cells. The results reveal that indeed SetDB1 primarily interacts with unmodified Bon which is by far more abundant compared to SUMOylated form . We think this experiment presents certain technical challenges, as the signal for Bon, when used as prey in co-IP experiments, is relatively faint, making it inherently difficult to detect the lower levels of SUMO-modified Bon. Additionally, in revised manuscript we have added new result of determining Bon interactors in ovary using mass-spec analysis, which showed that SetDB1 associates with wild-type, but not SUMO-deficient Bon. While our data support the idea that SUMO may contribute to Bon solubilization, possibly by disassembling aggregates, thereby indirectly facilitating its association with SetDB1 and chromatin, we acknowledge that the precise mechanism remains unclear.Reviewer #2 (Public Review):Summary:Drosophila ortholog of the TIF1 family of mammalian transcriptional regulators. Bon has been implicated in several developmental programs; however, the molecular details of its regulation have not been well understood. Here, the authors reveal the requirement of Bon in oogenesis, thus establishing a previously unknown biological function for this protein. Furthermore, careful molecular analysis convincingly established the role of Bon in transcriptional repression. This repressor function requires interactions with the NuRD complex and histone methyltransferase SetDB1, as well as sumoylation of Bon by the E3 SUMO ligase Su(var)2-10. Overall, this work represents a significant advance in our understanding of the functions and regulation of Bon and, more generally, the TIF1 family. Since Bon is the only TIF1 family member in Drosophila, the regulatory mechanisms delineated in this study may represent the prototypical and important modes of regulation of this protein family. The presented data are rigorous and convincing. As discussed below, this study can be strengthened by a demonstration of a direct association of Bon with its target genes, and by analysis of the biological consequences of the K20R mutation.The authors analyze the functions and regulation of Bon, the sole Strengths:1. This study identified the requirement for Bon in oogenesis, a previously unknown function for this protein.2. Identified Bon target genes that are normally repressed in the ovary, and showed that the repression mechanism involves the repressive histone modification mark H3K9me3 deposition on at least some targets.3. Showed that Bon physically interacts with the components of the NuRD complex and SetDB1. These protein complexes are likely mediating Bon-dependent repression.4. Identified Bon sumoylation site (K20) that is conserved in insects. This site is required for repression in a tethering transcriptional reporter assay, and SUMO itself is required for repression and interaction with SetDB1. Interestingly, the K20-mutant Bon is mislocalized in the nucleus in distinct puncta.5. Showed that Su(var)2-10 is a SUMO E3 ligase for Bon and that Su(var)2-10 is required for Bon-mediated repression.Weaknesses:The study would be strengthened by demonstrating a direct recruitment of Bon to the target genes identified by RNA-seq. Given that the global ChIP-seq was not successful, a few possibilities could be explored. First, Bon ChIP-qPCR could be performed on the individual targets that were functionally confirmed . Second, a global Bon ChIP-seq has been reported in PMID: 21430782 - these data could be used to see if Bon is associated with specific targets identified in this study. In addition, it would be interesting to see if there is any overlap with the repressed target genes identified in Bon overexpression conditions in PMID: 36868234.We greatly appreciate the reviewer's suggestion to demonstrate the direct recruitment of Bon to the target genes. As described in our answer to reviewer #1, we attempted to determine Bon direct targets using ChIP-seq approach using both native Bon antibodies and GFP-tagged Bon fly lines. However, analysis of ChIP-seq data did not reveal specific enrichment. Similarly, Bon ChIP-qPCR on individual targets showed the same results suggesting that Bon – similar to many other chromatin-bound proteins – are not amenable to ChIP protocol, at least in standard conditions. To further explore this issue, we have analyzed results of a global Bon ChIP-seq reported in PMID: 21430782. We did not find Bon binding to individual targets, but even more importantly, we did not see clear Bon enrichment elsewhere in the genome confirming a conclusion that Bon targets on chromatin cannot be determined by ChIP. Additionally, we explored the possibility of overlap between target genes repressed by Bon in our study and those observed under Bon overexpression conditions in PMID: 36868234. While we did identify 41 genes in common, it's important to note that the datasets are derived from different tissues , making direct comparison problematic.The second area where the manuscript can be improved is to analyze the biological function of the K20R mutant Bonus protein. The molecular data suggest that this residue is important for function, and it would be important to confirm this in vivo.We appreciate the reviewer's suggestion to analyze the biological function of the K20R mutant Bon protein. While we acknowledge that we did not use single-site K20R mutant for in vivo experiments, we demonstrated that the mutant with the three-residue substitution (3KR) is incapable of inducing repression . Given that other experiments consistently showed that K20 is the primarily SUMOylation site, this result supports the conclusion that K20 SUMOylation plays an important role in Bon-mediated transcriptional silencing.Reviewer #1 (Recommendations for The Authors):Make the RNAseq and ChIPseq data publicly available!The sequencing data have been deposited to the NCBI GEO archive. The accession number for all other RNA-seq and ChIP-seq data reported in this paper is GEO: GSE241375.Reviewer #2 (Recommendations for The Authors):It would be interesting to identify the biological basis of aberrant ovary development in Bon depletion conditions. Previous studies (e.g. PMID: 11336699) suggested that Bon loss of function clones are cell lethal, and the developmental defects in oogenesis presented in the current study offer an opportunity to delve more into the causes of cell loss, e.g. by showing that the cells die via apoptosis.Thank you for your valuable suggestion. In response to your comment, we performed a TUNEL assay to investigate whether germ cells in nos-Gal4>BonusKD ovaries undergo apoptosis. Our results indeed indicate that germ cells in these ovaries exhibit apoptosis, as evidenced by the TUNEL signal . This information has been included in the revised manuscript to provide insights into the biological basis of aberrant ovary development in Bon depletion conditions.The K20 residue could also be ubiquitinated. This possibility could at least be discussed, particularly given the presence of the RING Ub ligase domain in Bon that might potentially perform self-ubiquitination.Indeed, the possibility that Bon can be ubiquitinated is a valid consideration. We have explored this possibility. We did not detect any signals with the Ubiquitin antibody in both wild-type Bon immunoprecipitant and triple-mutant [3KR] ovaries  . This suggests that K20 is more likely responsible for Bon SUMOylation rather than ubiquitination. We appreciate the reviewer's suggestion and have included this information into the revised manuscript.


This study demonstrated that Renal iNUT has good specificity as a new tool for the nutrition screening of CKD patients, but its sensitivity needs to be optimized. Advanced age, high neutrophil–lymphocyte ratio, low transferrin level, low phase angle, and low body fat percentage are risk factors for malnutrition in patients with CKD. The combination of the above indicators has high diagnostic efficiency in the diagnosis of CKD malnutrition, which may be an objective, simple, and reliable method to evaluate the nutritional status of patients with CKD.Malnutrition is a risk factor for disease progression and poor prognosis in chronic kidney disease (CKD). However, the complexity of nutritional status assessment limits its clinical application. This study explored a new method of nutritional assessment in CKD (stage 1–5) patients using the Subjective Global Assessment (SGA) as the gold standard and evaluated its applicability. The kappa test was used to analyze the consistency of the Renal Inpatient Nutrition Screening Tool  with SGA and protein-energy wasting. Logistic regression analysis was used to analyze the risk factors of CKD malnutrition and calculate the prediction probability of multiple indicators combined for the diagnosis of CKD malnutrition. The receiver operating characteristic curve of the prediction probability was drawn to evaluate its diagnostic efficiency. A total of 161 CKD patients were included in this study. The prevalence of malnutrition according to SGA was 19.9%. The results showed that Renal iNUT had a moderate consistency with SGA and a general consistency with protein-energy wasting. Age > 60 years , neutrophil–lymphocyte ratio > 2.62 (OR = 3.862), transferrin < 200 mg/dL (OR = 4.222), phase angle < 4.5° (OR = 7.478), and body fat percentage < 10% (OR = 19.119) were risk factors for malnutrition in patients with CKD. The area under the receiver operating characteristic curve of multiple indicators for the diagnosis of CKD malnutrition was 0.89 (95% confidence interval: 0.834–0.946,  Chronic kidney disease (CKD) is a non-infectious disease with high incidence and poor prognosis. According to the analysis report of the Global Burden of Disease Chronic Kidney Disease Collaboration , there wThere is no unified standard for the definition of malnutrition in CKD patients, and the existing and validated nutritional assessment tools are rarely used for the nutritional assessment of CKD patients . In 2008The National Kidney Foundation’s Kidney Disease Outcomes Quality Initiative (KDOQI) nutrition guidelines for CKD in 2020  state thThis study aims to verify the applicability of Renal iNUT in the assessment of nutritional status in CKD (stage 1–5) patients, and to explore the related factors of malnutrition in CKD and the diagnostic efficacy of multiple indicators combined in the diagnosis of CKD malnutrition.A total of 187 patients with CKD who were hospitalized in the Department of Nephrology of the First Medical Center of the Chinese People’s Liberation Army General Hospital from March 2022 to September 2022 were enrolled in this study. Inclusion criteria: (1) patients diagnosed with CKD according to the 2012 KDIGO clinical practice guidelines ; (2) ageThe general data of subjects such as gender, age, height, weight, duration of nephropathy, and history of diabetes mellitus were collected. Venous blood samples were collected after fasting on the second day of admission to determine white blood cells (WBCs), neutrophil–lymphocyte ratio (NLR), C reactive protein (CRP), interleukin-6 (IL-6), hemoglobin, total protein, albumin, blood urea nitrogen (BUN), serum creatinine, estimated glomerular filtration rate , cystatBMI was calculated by dividing the weight (in kilograms) by the square of the height (in meters).HGS: According to the size of the subject’s hand, the handle of the handgrip dynamometer was adjusted, the subject was informed to take the standing position with the arm naturally sagging, and the handgrip dynamometer was grasped with the unilateral hand as hard as possible. The measurement was accurate to 0.1 kg and repeated three times with an interval of 1 min, and the highest value was taken as the HGS value.CC: The maximum circumference was measured with a tape measure at the right calf of the subject in a sitting position with feet on the floor and knees bent at 90°. The measurement was repeated twice and averaged with an accuracy of 0.1 cm.TSF: The subject’s arm was naturally pendulous, the surveyor pinched the sebum at the midpoint of the dorsal upper arm of the subject with the left thumb and index finger, and they then measured the skinfold thickness with a sebum skinfold caliper at a distance of 1 cm from the finger pinching site. The tip of the caliper was made to fully clamp the skinfold, the results after the pointer came to a complete stop were read and recorded immediately, and the measurements were repeated three times and averaged with an accuracy of 0.1 mm.The body composition indicators of the subjects were collected by the InbodyS10 body composition analyzer, including mid-arm circumference (MAC), MAMC, skeletal muscle mass index (SMI), body protein, body inorganic salts, body bone mineral content, body fat, BFP, and PhA. Before measurement, it was confirmed whether there was no pacemaker or metal implant in the subject, and the subject was informed to take the supine position, exposing the bilateral fingers and ankles. The relevant information of the subject was input on the instrument operation panel, the upper-limb electrode clips were clamped on the thumb and middle finger of the subject, the lower-limb electrode clips were clamped on the ankle of the subject, and the measurement was started after confirming that the electrode clips were properly clamped. After completion of the measurement, the electrode clips were removed, and the body composition report was read.The data on BMI, handgrip strength (HGS), calf circumference (CC), TSF, and body composition of the participants were collected, and the specific calculation and measurement methods were as follows:The program content for SGA, PEW, and Renal iNUT was gathered by trained clinicians. The assessment of SGA included five items of medical history  and three items of physical examination  . ParticiAccording to the diagnostic criteria of PEW formulated by ISRNM , it inclRenal iNUT  includest-tests. Non-normally distributed data were expressed as the median with interquartile range and analyzed using the Mann–Whitney U test. Count variables were expressed as frequency and percentages and analyzed using chi-square or Fisher’s exact test. The kappa test was used to analyze the consistency of Renal iNUT with SGA and PEW . Logistic regression analysis was used to analyze the related factors of CKD malnutrition and calculate the prediction probability of multiple indicators combined for the diagnosis of CKD malnutrition. The receiver operating characteristic (ROC) curve of the prediction probability was drawn to evaluate its diagnostic efficiency. The statistical analyses were performed using SPSS version 26.0 for Mac . Statistical significance was set at p < 0.05.The measurement data with the normal distribution were described by mean ± standard deviation and were analyzed using Student’s A total of 187 CKD patients hospitalized in the Department of Nephrology of the First Medical Center of the Chinese People’s Liberation Army General Hospital from March 2022 to September 2022 were selected. After excluding 3 cases without nutritional status assessment, 19 cases without body composition, and 4 cases missing dietary recall, 161 subjects were finally included. The subject screening process is shown in Among the 161 CKD patients, 46 (28.6%) were at the CKD1 stage, 33 (20.5%) at the CKD2 stage, 47 (29.2%) at the CKD3 stage, 17 (10.6%) at the CKD4 stage, and 18 (11.2%) at the CKD5 stage. As shown in n = 32), 19.9% (n = 32), and 21.7% (n = 35), respectively, and there was no significant difference between the gender groups (p > 0.05), as shown in The prevalence of malnutrition diagnosed according to SGA, PEW, and Renal iNUT was 19.9% (n = 67) had reduced functional capacity, 37.9% (n = 61) had a loss of subcutaneous fat, and 23.6% (n = 38) had edema. There were 29 (18%), 20 (12.4%), and 11 (6.8%) cases of muscle wasting, reduced dietary intake, and weight loss, respectively. None of the SGA items showed statistical differences between gender group comparisons.According to SGA, all subjects (100%) had a low stress of metabolic demand, 41.6%  of the participants had inadequate dietary intake, and 59% (n = 95) had subnormal serum chemistry. Fifty-five participants (34.2%) had decreased body mass and 17 (10.6%) had muscle mass loss. The proportion of participants with decreased body mass was higher in females than in males .In the diagnosis of PEW, the majority (n = 85) of the subjects took nutritional supplements, and 21 (13%), 18 (11.2%), and 16 (9.9%) subjects had unintentional weight loss, poor appetite, and a BMI less than or equal to 20 kg/m2, respectively. Among gender groups, the proportion of female subjects with a BMI less than or equal to 20 kg/m2 was significantly higher than that of male subjects .In the assessment of Renal iNUT, 52.8% (p < 0.001). Compared with SGA, Renal iNUT had a sensitivity of 59.4%, a specificity of 87.6%, a positive predictive value of 54.3%, and a negative predictive value of 89.7% in diagnosing malnutrition (p < 0.001). Compared with PEW, Renal iNUT had a sensitivity of 46.9%, a specificity of 84.5%, a positive predictive value of 42.9%, and a negative predictive value of 86.5% for diagnosing malnutrition , as shown in p > 0.05).According to the SGA, the subjects were classified as malnutrition and non-malnutrition. Compared with the non-malnutrition group, the levels of NLR, IL-6, BUN, cystatin C, and serum phosphorus in the malnutrition group were higher, while the levels of hemoglobin, total protein, albumin, prealbumin, transferrin, eGFR, serum calcium, and dietary energy intake were lower (p < 0.05). There were no statistically significant differences in TSF, SMI, body protein, body inorganic salts, body bone mineral content, and BFP between the two groups  and the prediction probability P of multiple indicators combined for the diagnosis of CKD malnutrition were calculated (Equations (1) and (2)). The area under the curve (AUC) of the prediction probability was 0.89 : 0.834–0.946, p < 0.001), as shown in According to the results of multivariate logistic regression analysis of CKD malnutrition, the score Logit and body cell mass caused by lack of nutrient intake”, but there is no clear and generally accepted diagnostic criteria for malnutrition . In 2017It has been reported that the prevalence of malnutrition in patients with stage CKD3-5 ranges from 11% to 54% worldwide , and the2” project (21% vs. 3%). It is worth exploring whether gender differences should be considered in the definition of BMI in the nutrition assessment.SGA is considered to be the most effective tool for nutrition assessment of hospitalized patients, and it was commonly used as the “gold standard” in the study . PEW is p < 0.001). The diagnosis of multiple indicators combined may be a simple, objective, and reliable method to evaluate the nutritional status of CKD.In the multivariate logistic regression analysis, age, NLR, transferrin, PhA, and BFP were associated with CKD malnutrition, and the combination of the above indicators had high diagnostic efficacy in the diagnosis of CKD malnutrition . The risk of malnutrition in CKD patients over 60 years old was 6.78 times higher than that in those under 60 years old . The study by Xi et al. [Aging is one of the risk factors for malnutrition. The prevalence of malnutrition in elderly inpatients is significantly higher than that in young patients. It was reported that the prevalence of malnutrition was 1.2–2.3 times higher in patients over 65 years old than in those under 65 years old . Variousi et al.  also foup = 0.011), and NLR ≥ 2.62 could be used to identify CKD malnutrition. This study similarly found that NLR was higher in malnutrition CKD patients than in non-malnutrition patients. Taking 2.62 as the cut-off value of NLR, the risk of malnutrition in CKD patients with NLR > 2.62 was 3.862 times higher than that in patients with NLR ≤ 2.62 .NLR is a biomarker reflecting the balance between two aspects of the immune system: acute and chronic inflammation (such as neutrophil count) and adaptive immunity (lymphocyte count) . NLR hasp = 0.001), there was also a significant difference between the two groups in transferrin , and low transferrin level (<200 mg/dL) was a risk factor for malnutrition in CKD.Both hemoglobin and transferrin are indicators of anemia. The study by Ucha et al.  showed t2 was used as a diagnostic criterion for malnutrition, and the BMI cutoffs for assessing malnutrition were divided according to age  but need to consider racial and regional differences. TSF could be used to reflect the reserve of human subcutaneous fat, and MAC and MAMC are indicators of muscle consumption. MAMC and computed tomography have good consistency in assessing muscle mass in CKD patients [p < 0.001). Our study also found that PhA was significantly lower in the malnutrition group than in the non-malnutrition group . Studies by Bansal et al. [Anthropometric measurements are integral parts of the CKD nutritional assessment. BMI is commonly used to assess nutritional status and obesity. In the 2015 consensus of the European Society of Clinical Nutrition and Metabolism , a BMI opatients . Cupparipatients  found thpatients ,18,19,41l et al.  and Barrl et al.  demonstrl et al.  showed tIn order to provide a relatively objective, simple, and reliable method for the assessment of nutrition status in CKD patients, this study verified the applicability of renal iNUT in the CKD population for the first time. Moreover, we collected comprehensive data including clinical laboratory indicators, anthropometry, and body composition indicators to describe the nutritional status of CKD patients and evaluate the diagnostic value of multiple indicators combined in the diagnosis of CKD malnutrition. There are some limitations in this study. First, this study is a single-center study, and the study population is relatively limited. Multi-center studies can be carried out to verify the method of multiple indicators combined for the diagnosis of CKD malnutrition in a wider population, to make the results of the study more representative in the future. Second, it is necessary to expand the sample size and reduce sample bias to make the study results more reliable. At the same time, a follow-up cohort can be established to further explore the relationship between the related factors of CKD malnutrition and the progression and prognosis of CKD.This study shows that Renal iNUT has good specificity as a new tool for nutrition screening in CKD patients, but its sensitivity needs to be optimized. Advanced age (>60 years), high NLR (≥2.62), low transferrin level (<200 mg/dL), low PhA (<4.5°), and low BFP (<10%) are risk factors for CKD malnutrition. The combination of the above indicators has high diagnostic efficiency in the diagnosis of CKD malnutrition. The diagnosis of multiple indicators combined may be an objective, simple, and reliable method to evaluate the nutritional status of CKD patients.