Enhanced Production and Profiling of Ganoderic Acids in Ganoderma lucidum Mycelia via Two-Stage Cultivation and GNPS-Guided Metabolomics

Round 1

Reviewer 1 Report

Major revision required. The scientific findings are potentially interesting, but the manuscript must address the statistical rigor, tone down novelty claims , and correct the writing/formatting issues before it can be accepted for publication.

The manuscript identifies a promising high-ganoderic acid-producing strain of Ganoderma lucidum and presents valuable data on cultivation optimization and heat-induced chemical conversion. However, several methodological, presentational, and statistical issues need to be addressed before acceptance. 

1. Figure 1c (volcano plot) – The number of biological replicates used for the comparison between TM701 and BCRC 36203 is not specified in the figure legend or main text. The volcano plot threshold (fold change > 1.2, p < 0.05) is relatively loose, and no correction for multiple comparisons (e.g., FDR) has been applied. This may inflate the number of significantly enriched features.

2. Figure 2 and Figure 3 – Although the text mentions n = 5 in the legend, it is not stated whether these are biological or technical replicates. For time‑course data, it is also unclear whether each time point represents independent cultures or repeated measurements from the same batch.

3. LC‑MS batch quality control – No information is provided on the use of pooled QC samples, retention time drift, or peak area variation across runs. Such QC data are essential for untargeted metabolomics workflows.

4. GNPS molecular network – The number of replicate injections per group (G1 and G2) is mentioned as “triplicate uploads”, but it is not explained how these replicates were combined or whether spectral counts were averaged. The pie‑chart node colors would be more informative if error or variance were indicated。

5. “First application of GNPS for comparison of triterpenoid profiles between Ganoderma strains” – A literature search reveals that GNPS molecular networking has already been used for comparative metabolomics of Ganoderma species (e.g., comparative analysis of different Ganoderma strains or cultured vs. wild specimens). The authors should cite such prior work and reframe the novelty as “an additional demonstration” or “application to strain screening”.

6. Duplicated section heading – On page 4, the heading “3.1. Strain Comparison and Metabolic Profiling of G. lucidum Mycelial Cultures” appears twice (immediately after the first paragraph of section 3.1). This is likely a copy‑paste error.

7. Inconsistent use of abbreviations – The full term “Global Natural Products Social Molecular Networking” is given in the abstract but not consistently abbreviated to GNPS thereafter; the abbreviation is introduced but later the full name reappears (e.g., in the conclusions). Standardize to GNPS after first definition.

8. Reference formatting inconsistencies – Some references lack journal abbreviations (e.g., Ref. 25 includes “Food Biosci.” while others use full names). Volume and page numbers are occasionally missing or incomplete. The authors should follow the journal’s reference style strictly.

9. Language and grammar – Several sentences are overly long or ambiguous. For example, in the abstract: “Using Global Natural Products Social Molecular Networking, we identified a high- triterpenoid- producing strain, G. lucidum TM701, which accumulated 99 GA derivatives…” – the spacing around hyphens is irregular (“high- triterpenoid- producing” should be “high‑triterpenoid‑producing” or rephrased). A thorough language polish is recommended.

10. Figure callouts – In the text, Figure 2 and Figure 3 are referenced, but the figure legends are missing details as noted under Point 4. Also, Figure S5 is mentioned in the text but its significance is not sufficiently explained in the main results.

Author Response

Comments 1: The manuscript identifies a promising high-ganoderic acid-producing strain of Ganoderma lucidum and presents valuable data on cultivation optimization and heat-induced chemical conversion. However, several methodological, presentational, and statistical issues need to be addressed before acceptance.
Response 1: We sincerely appreciate the reviewer’s recognition.

Comments 2: Figure 1c (volcano plot) – The number of biological replicates used for the comparison between TM701 and BCRC 36203 is not specified in the figure legend or main text. The volcano plot threshold (fold change > 1.2, p < 0.05) is relatively loose, and no correction for multiple comparisons (e.g., FDR) has been applied. This may inflate the number of significantly enriched features.
Response 2: Thank you for your valuable suggestion. The volcano plot was constructed using data obtained from three independent biological replicates for each strain, and this information has been added to the caption of Figure 1(c). Please refer to line 174 in the revised manuscript. We also appreciate the reviewer’s comment regarding the statistical threshold. We selected a fold-change threshold of |log2FC| > 1.2 based on previous metabolomics studies that adopted comparable or even less stringent criteria (e.g., |log2FC| > 1.0) [1]. We also evaluated a more stringent threshold (|log2FC| > 1.5) and found that the overall differences between TM701 and BCRC 36203 remained clearly distinguishable. Therefore, we believe that the current threshold is appropriate for illustrating the overall metabolic differences between the two strains and have retained it in the revised manuscript. To control the false discovery rate (FDR) resulting from multiple hypothesis testing across the 511 features, raw p-values were adjusted using the Benjamini–Hochberg (BH) correction method [2]. Features with a BH-adjusted p-value (q-value) less than 0.05 were defined as statistically significant.

Comments 3: Figure 2 and Figure 3 – Although the text mentions n = 5 in the legend, it is not stated whether these are biological or technical replicates. For time‑course data, it is also unclear whether each time point represents independent cultures or repeated measurements from the same batch.
Response 3: Thank you for the suggestion. All data were obtained from five independent biological replicates (n = 5). For the time-course experiments, each time point represents the average of five independent cultures. We have revised the relevant description accordingly. Please refer to line 97 on page 3 of the revised manuscript.

Comments 4: LC‑MS batch quality control – No information is provided on the use of pooled QC samples, retention time drift, or peak area variation across runs. Such QC data are essential for untargeted metabolomics workflows.
Response 4: We thank the reviewer for this important comment. We agree that pooled QC samples are commonly used to monitor retention time drift and peak area variation in untargeted metabolomics workflows. In the present study, pooled QC samples were not included, which we acknowledge as a limitation of the analytical workflow. To reduce inter-batch variation, all study samples were analyzed within the same LC-MS analytical batch under identical chromatographic and mass spectrometric conditions. Therefore, no cross-batch correction was applied. Accordingly, the metabolomics results are interpreted as exploratory findings, and key candidate metabolites should be further validated in future studies using a dedicated targeted assay with appropriate QC procedures. We have revised Section 2.3 to improve its clarity. Please refer to lines 115–117 on page 3 of the revised manuscript.

Comments 5: GNPS molecular network – The number of replicate injections per group (G1 and G2) is mentioned as “triplicate uploads”, but it is not explained how these replicates were combined or whether spectral counts were averaged. The pie‑chart node colors would be more informative if error or variance were indicated。
Response 5: Thank you for your valuable suggestion. We have revised Section 2.6 to clarify how the replicate LC–MS/MS datasets were processed in GNPS. For each strain, three independent biological replicate LC–MS/MS files were uploaded to GNPS as separate datasets. These replicate files were not averaged or merged before molecular networking. Please refer to lines 142–143 on page 4 of the revised manuscript. The raw LC–MS/MS data and the resulting GNPS molecular network are publicly available at: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=f3a43a0ea4ff45ed9a6f3caceb1c95df. The node pie charts provide a direct visualization of the relative distribution of each molecular feature among the sample groups and are not originally designed to display replicate variability. Therefore, error bars are not incorporated into the GNPS molecular network visualization. To facilitate the review process, we have also provided the raw LC–MS/MS data for all biological replicates as an Excel file through an OSF repository for the reviewers' reference (https://osf.io/zyhxu/overview?view_only=89cb204366c94d209057ece6bced885d).

Comments 6: “First application of GNPS for comparison of triterpenoid profiles between Ganoderma strains” – A literature search reveals that GNPS molecular networking has already been used for comparative metabolomics of Ganoderma species (e.g., comparative analysis of different Ganoderma strains or cultured vs. wild specimens). The authors should cite such prior work and reframe the novelty as “an additional demonstration” or “application to strain screening”.
Response 6: Thank you for your valuable suggestion. We have revised the Introduction accordingly by citing previous studies that applied GNPS molecular networking to Ganoderma metabolomics. We also clarified that, although GNPS has been previously used for comparative analyses of Ganoderma species, its application to strain-level screening of mycelial triterpenoid profiles remains limited. Please refer to lines 56–62 on page 2 of the revised manuscript.

Comments 7: Duplicated section heading – On page 4, the heading “3.1. Strain Comparison and Metabolic Profiling of G. lucidum Mycelial Cultures” appears twice (immediately after the first paragraph of section 3.1). This is likely a copy‑paste error.
Response 7: Thank you for the suggestion. We have revised the manuscript accordingly.

Comments 8: Inconsistent use of abbreviations – The full term “Global Natural Products Social Molecular Networking” is given in the abstract but not consistently abbreviated to GNPS thereafter; the abbreviation is introduced but later the full name reappears (e.g., in the conclusions). Standardize to GNPS after first definition.
Response 8: Thank you for the suggestion. We have revised the manuscript accordingly.

Comments 9: Reference formatting inconsistencies – Some references lack journal abbreviations (e.g., Ref. 25 includes “Food Biosci.” while others use full names). Volume and page numbers are occasionally missing or incomplete. The authors should follow the journal’s reference style strictly.
Response 9: Thank you for the suggestion. We have revised the references accordingly.

Comments 10: Language and grammar – Several sentences are overly long or ambiguous. For example, in the abstract: “Using Global Natural Products Social Molecular Networking, we identified a high- triterpenoid- producing strain, G. lucidum TM701, which accumulated 99 GA derivatives…” – the spacing around hyphens is irregular (“high- triterpenoid- producing” should be “high‑triterpenoid‑producing” or rephrased). A thorough language polish is recommended.
Response 10: Thank you for the suggestion. We have carefully reviewed and polished the language throughout the entire manuscript, including the Abstract, to improve clarity, readability, and grammatical accuracy.

Comments 11: Figure callouts – In the text, Figure 2 and Figure 3 are referenced, but the figure legends are missing details as noted under Point 4. Also, Figure S5 is mentioned in the text but its significance is not sufficiently explained in the main results.
Response 11: Thank you for your suggestion. We have added an explanation of the biological replicates (n = 5) in the Materials and Methods section. Please refer to line 97 on page 3 of the revised manuscript. We have also revised the caption of Figure 3 and Figure 4 (original Figure 2 and Figure 3) to clarify the definition of PDB and dPDB groups (line 263 and 286). In addition, an explanation of Figure S6 (original Figure S5) has been added to lines 312–315 on page 8 of the revised manuscript.

Reference

1. Bondzie-Quaye, P.; Huang, Q. Transcriptomic and metabolomic profiling of heat stress responses and ganoderic acid biosynthesis in Ganodermalucidum. Appl. Biochem. Biotechnol. 2026, 198, 4421-4448. https://doi.org/10.1007/s12010-026-05668-z.
2. Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 1995, 57, 289-300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.

Reviewer 2 Report

The manuscript fully corresponds to the subject and level of the Journal of Fungi. It can be accepted for publication after a revision, especially of the Figures.

The drawings contain a lot of valuable information, including the structures of the joints. However, they are poorly readable and this makes it difficult to understand the manuscript.

Figure 1 contains small fragments that are difficult to read. I think it's possible to divide it into two or three figures.
Figure 3a and 3b - I suggest that the authors change the scale of the Y-axis to make the graphs look better.
Figure 4 is also unreadable. The connection structures are very small.

Author Response

Comments 1: The drawings contain a lot of valuable information, including the structures of the joints. However, they are poorly readable and this makes it difficult to understand the manuscript. Figure 1 contains small fragments that are difficult to read. I think it's possible to divide it into two or three figures.
Response 1: Thank you for your valuable suggestion. We have separated the original Figure 1 into two figures to improve readability. The GNPS molecular networking results are now presented separately as Figure 2. Please refer to lines 167 and 192 on pages 4 and 5 of the revised manuscript. In addition, because the complete GNPS molecular network is publicly available through the GNPS repository (as described in line 143), we have moved the full network figure to Supplementary Figure S4 to improve readability of the main text.

Comments 2: Figure 3a and 3b - I suggest that the authors change the scale of the Y-axis to make the graphs look better.
Response 2: Thank you for your valuable comment. We appreciate this suggestion. However, the y-axis scales in the original Figure 3(a) and (b) (now Figure 4) were intentionally kept consistent with those in the original Figure 2 (now Figure 3). This allows direct comparison of biomass accumulation and reducing sugar consumption between the PDB-based and diluted PDB-based cultivation conditions.

Comments 3: Figure 4 is also unreadable. The connection structures are very small.
Response 3: Thank you for your suggestion. We have revised Figure 5 (original Figure 4) by enlarging the chemical structures to improve their readability. We retained Figures 5(a) and 5(b) in the same figure because the peak numbers in the LC chromatograms correspond directly to the compound numbers shown in the proposed transformation scheme, making side-by-side comparisons easier for readers.

Reviewer 3 Report

This manuscript presents a technically sound and industrially relevant study on the high-level production of ganoderic acids (GAs) using a Ganoderma lucidum strain TM701. The integration of GNPS-based molecular networking with two-stage submerged–static cultivation is well executed, and the reported GA yield (~1.4 g/L) exceeds most previously published values for mycelial cultures. However, several clarifications regarding strain novelty, quantitative rigor, and causal attribution are required.

1. The manuscript states that G. lucidumTM701 was provided by Wishsun Natural Farm. The authors should clarify whether this strain was obtained through artificial breeding (selective screening) or isolated from a natural environment.
2. While the GA yield is notably high, the manuscript fails to distinguish whether this increase is due to the genetic characteristics of the TM701 strain or the modified two-stage cultivation strategy. A comparative experiment using the reference strain (BCRC 36203) under the exact same optimized conditions is necessary to validate the intrinsic productivity of TM701. Based on the current data, it is unclear if the high yield is strain-specific or process-specific.
3. All ganoderic acids (GA) contents are expressed as GA-A equivalents based on UV absorbance at 245 nm. The authors must explicitly state in Sections 2.4 and 3.3 that these values represent relative quantification, not absolute mass concentrations, due to varying molar absorptivities among GA analogues.
4. The manuscript identifies 99 GA-related nodes but lacks annotation confidence levels. The authors should adopt the Sumner et al. (2020) classification (Level 1–3) and provide detailed MS/MS fragmentation interpretations for the four marker GAs (GA-Mb/Mc, GA-S/Mf, GA-T, and GA-R).
5. Critical experimental details are missing. The physicochemical properties of the wheat bran infusion (initial pH, total sugar, total nitrogen) must be reported. Additionally, environmental parameters for static cultivation (container sealing, light exposure) require clarification.
6. Figures 2 and 3 lack statistical significance markers.
7. The reporting units in Table S3 are inconsistent. All GA content data should be standardized to a single unit—either mg L⁻¹ or mg g⁻¹ DW—throughout the table.
8. The GA-Mb/Mc→GA-Mh→GA-P/Q conversion route is presented as conclusive. This should be explicitly described as a proposed (speculative) transformation route until validated by pure-compound heating experiments or isotopic tracing studies.

Author Response

Comments 1: The manuscript states that G. lucidum TM701 was provided by Wishsun Natural Farm. The authors should clarify whether this strain was obtained through artificial breeding (selective screening) or isolated from a natural environment.
Response 1: Thank you for your valuable suggestion. G. lucidum TM701 was originally isolated from a natural environment. We have revised Section 2.1 to include this information. Please refer to line 76 on page 2 of the revised manuscript.

Comments 2: While the GA yield is notably high, the manuscript fails to distinguish whether this increase is due to the genetic characteristics of the TM701 strain or the modified two-stage cultivation strategy. A comparative experiment using the reference strain (BCRC 36203) under the exact same optimized conditions is necessary to validate the intrinsic productivity of TM701. Based on the current data, it is unclear if the high yield is strain-specific or process-specific.
Response 2: Thank you for your valuable comment. We agree that comparing TM701 and the reference strain BCRC 36203 under the same optimized cultivation conditions would provide a more definitive assessment of the relative contributions of strain characteristics and cultivation strategy to GA production. However, the primary objective of the present study was to identify and characterize a high-GA-producing G. lucidum strain using GNPS-guided metabolomic profiling, followed by cultivation optimization of the selected strain. Under the same baseline cultivation conditions, TM701 exhibited higher triterpenoid abundance and greater GA diversity than BCRC 36203, as described in Sections 3.1 and 3.2. Based on these results, TM701 was selected for subsequent cultivation optimization. We have therefore revised the manuscript to avoid overinterpreting the optimized GA yield as being solely attributable to intrinsic strain productivity. Instead, the high GA production is now described as resulting from the combination of the high-producing characteristics of TM701 and the modified two-stage cultivation strategy. A direct comparison of TM701 and BCRC 36203 under the optimized conditions will be addressed in future work. We sincerely appreciate the reviewer's constructive suggestion.

Comments 3: All ganoderic acids (GA) contents are expressed as GA-A equivalents based on UV absorbance at 245 nm. The authors must explicitly state in Sections 2.4 and 3.3 that these values represent relative quantification, not absolute mass concentrations, due to varying molar absorptivities among GA analogues.
Response 3: Thank you for your suggestion. We have clarified that the reported GA content and production values represent relative quantification expressed as GA-A equivalents, rather than absolute mass concentrations of individual GA analogues. We have added this clarification to the legends of Figures 3 and 4 (formerly Figures 2 and 3) and revised the Results and Discussion section accordingly. Please refer to lines 268-269, 291-293, and 297-299 on page 7 and page 8 of the revised manuscript.

Comments 4: The manuscript identifies 99 GA-related nodes but lacks annotation confidence levels. The authors should adopt the Sumner et al. (2020) classification (Level 1–3) and provide detailed MS/MS fragmentation interpretations for the four marker GAs (GA-Mb/Mc, GA-S/Mf, GA-T, and GA-R).
Response 4: Thank you for your valuable suggestion. We have revised the manuscript to clarify the metabolite annotation confidence levels according to the criteria proposed by Sumner et al. (2007) [1]. Among the 99 GA-related molecular network nodes, 21 triterpenoid species, including several isomers shown in Figure S5, were assigned as Level 2 annotations (putatively annotated compounds). Since authentic reference standards were not available for all compounds, we manually compiled an in-house reference database of Ganoderma triterpenoids from previously published MS studies [2-5]. This database summarizes the molecular formulas, expected precursor ions, characteristic neutral losses, and diagnostic fragment ions reported for individual triterpenoids, as well as fragmentation patterns commonly observed in Ganoderma triterpenoids. The observed MS/MS spectra were interpreted based on the fragmentation patterns obtained under our LC–MS/MS conditions (negative ionization mode and the chromatographic conditions used in this study) and compared with the in-house reference database together with publicly available MS spectral databases. Therefore, the compound annotations were assigned based on accurate mass measurements, diagnostic MS/MS fragmentation patterns, and comparison with published literature, rather than direct confirmation using authentic reference standards. The in-house reference database has been deposited in the Open Science Framework as an Excel file and is publicly available at: https://osf.io/rsvyx/overview?view_only=13d74a94312c455da85a79986e3ab6fd. Please refer to lines 203–212 on page 5 of the revised manuscript.

Comments 5: Critical experimental details are missing. The physicochemical properties of the wheat bran infusion (initial pH, total sugar, total nitrogen) must be reported. Additionally, environmental parameters for static cultivation (container sealing, light exposure) require clarification.
Response 5: Thank you for your valuable comment. We have revised Section 2.2 to provide additional details regarding the first-stage wheat bran infusion and the second-stage static cultivation conditions. In the present two-stage process, the wheat bran infusion was used as the first-stage medium for submerged biomass preparation, whereas GA accumulation was mainly evaluated during the second-stage static cultivation. Therefore, the first-stage parameters were monitored primarily to confirm the fermentation status before transfer to the second stage. The pH and dissolved oxygen profiles during first-stage cultivation have been added as Figure S6(b), and the manuscript has been revised accordingly. Please refer to lines 238–240 on page 6 of the revised manuscript. We also clarified the environmental conditions for the second-stage static cultivation. The cultivation bottles were covered with cotton plugs to allow gas exchange and were therefore not completely sealed. All static cultivation was performed in the dark at 30 °C and 80–85% relative humidity. The appearance of the cultivation bottles is shown in Figure S2. Please refer to lines 95–98 on page 3 of the revised manuscript.

Comments 6: Figures 2 and 3 lack statistical significance markers.
Response 6: Thank you for your valuable comment. We agree that statistical significance markers should be used when specific pairwise comparisons are claimed. The primary purpose of Figures 3 and 4 (original Figures 2 and 3) is to present the time-course profiles of biomass accumulation, reducing sugar consumption, GA content, and GA production under different cultivation conditions, rather than to emphasize individual pairwise comparisons at each time point. To avoid overinterpretation, we have revised the Results and Discussion section to focus on the observed temporal trends and maximum values achieved under each condition, and we have removed wording that may imply statistical significance, such as “significantly,” where no corresponding statistical test was presented. The data are presented as mean ± SD from five independent biological replicates to show reproducibility and biological variation. Please refer to line 256 on page 6 of the revised manuscript.

Comments 7: The reporting units in Table S3 are inconsistent. All GA content data should be standardized to a single unit—either mg L⁻¹ or mg g⁻¹ DW—throughout the table.
Response 7:  Thank you for your valuable comment. We agree that the reporting units should be clearly and consistently defined to avoid confusion. We have therefore clarified the terminology and retained both units because they represent two different parameters rather than inconsistent measurements of the same parameter. GA content (mg g⁻¹ DW) indicates the amount of ganoderic acids accumulated per unit dry weight of mycelia, reflecting the biosynthetic capacity of the fungal biomass. In contrast, GA production (mg L⁻¹) represents the total amount of ganoderic acids produced per unit culture volume after the second-stage static cultivation and therefore incorporates the effect of biomass accumulation. These two parameters are related by the equation: GA production (mg L⁻¹) = GA content (mg g⁻¹ DW) × Biomass (g L⁻¹). Therefore, reporting both units provides complementary information and allows independent evaluation of GA biosynthetic capacity and overall production yield. Throughout the manuscript, the reporting units are used consistently. Specifically, GA content is always expressed as mg g⁻¹ DW, whereas GA production is consistently expressed as mg L⁻¹.

Comments 8: The GA-Mb/Mc→GA-Mh→GA-P/Q conversion route is presented as conclusive. This should be explicitly described as a proposed (speculative) transformation route until validated by pure-compound heating experiments or isotopic tracing studies.
Response 8: Thank you for the suggestion. We agree with you. Therefore, we have revised the caption of Figure 5 (original Figure 4) to explicitly describe this route as a proposed transformation route. Please refer to lines 331–337 on page 9 of the revised manuscript.

Reference

1. Sumner, L.W.; Amberg, A.; Barrett, D.; Beale, M.H.; Beger, R.; Daykin, C.A.; Fan, T.W.-M.; Fiehn, O.; Goodacre, R.; Griffin, J.L. Proposed minimum reporting standards for chemical analysis: Chemical analysis working group (cawg) metabolomics standards initiative (msi). Metabolomics. 2007, 3, 211-221.
2. Tang, W.; Gu, T.; Zhong, J.J. Separation of targeted ganoderic acids from ganoderma lucidum by reversed phase liquid chromatography with ultraviolet and mass spectrometry detections. Biochemical Engineering Journal. 2006, 32, 205-210. https://doi.org/10.1016/j.bej.2006.09.026
3. Keypour, S.; Rafati, H.; Riahi, H.; Mirzajani, F.; Moradali, M.F. Qualitative analysis of ganoderic acids in ganoderma lucidum from iran and china by rp-hplc and electrospray ionisation-mass spectrometry (esi-ms). Food chemistry. 2010, 119, 1704-1708. https://doi.org/10.1016/j.foodchem.2009.09.058
4. Biswal, R.P.; Dandamudi, R.B.; Patnana, D.P.; Pandey, M.; Vutukuri, V.R.K. Metabolic fingerprinting of ganoderma spp. Using uhplc-esi-qtof-ms and its chemometric analysis. Phytochemistry. 2022, 199, 113169. https://doi.org/10.1016/j.phytochem.2022.113169
5. Hirotani, M.; Asaka, I.; Ino, C.; Furuya, T.; Shiro, M. Ganoderic acid derivatives and ergosta-4, 7, 22-triene-3, 6-dione from ganoderma lucidum.Phytochemistry. 1987, 26, 2797-2803. https://doi.org/10.1016/S0031-9422(00)83593-1

Round 2

Reviewer 1 Report

The authors had made the correction, and it could be accepted for publication.

no more.

Reviewer 2 Report

The revised manuscript can be accepted for publication.

The authors took into account the comments of the reviewers and significantly improved the manuscript.

Reviewer 3 Report

No additional modifications are recommended for the current revised version.

No additional modifications are recommended for the current revised version.